Triple
T13839003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power |
E332601
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Lela Loren
Lela Loren is an American actress best known for her role as Angela Valdes on the crime drama television series "Power."
|
E1065639
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Lela Loren | Statement: [Power, starring, Lela Loren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lela Loren Context triple: [Power, starring, Lela Loren]
-
A.
Diana Sands
Diana Sands was an acclaimed American stage and screen actress best known for her groundbreaking performance in the original Broadway production and film adaptation of "A Raisin in the Sun."
-
B.
Luana Patten
Luana Patten was an American child actress best known for her early work in Walt Disney films during the 1940s and 1950s.
-
C.
Jo Harlow
Jo Harlow is a technology executive best known for leading mobile device and smartphone businesses at companies such as Nokia and later Microsoft.
-
D.
Lela Rogers
Lela Rogers was an American journalist, screenwriter, and acting coach best known as the mother and early career mentor of Hollywood star Ginger Rogers.
-
E.
Ava Paige
Ava Paige is the calculating and morally ambiguous leader of the WCKD organization in the Maze Runner series, orchestrating experiments on immune youths to find a cure for the Flare virus.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lela Loren Triple: [Power, starring, Lela Loren]
Generated description
Lela Loren is an American actress best known for her role as Angela Valdes on the crime drama television series "Power."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lela Loren Target entity description: Lela Loren is an American actress best known for her role as Angela Valdes on the crime drama television series "Power."
-
A.
Diana Sands
Diana Sands was an acclaimed American stage and screen actress best known for her groundbreaking performance in the original Broadway production and film adaptation of "A Raisin in the Sun."
-
B.
Luana Patten
Luana Patten was an American child actress best known for her early work in Walt Disney films during the 1940s and 1950s.
-
C.
Jo Harlow
Jo Harlow is a technology executive best known for leading mobile device and smartphone businesses at companies such as Nokia and later Microsoft.
-
D.
Lela Rogers
Lela Rogers was an American journalist, screenwriter, and acting coach best known as the mother and early career mentor of Hollywood star Ginger Rogers.
-
E.
Ava Paige
Ava Paige is the calculating and morally ambiguous leader of the WCKD organization in the Maze Runner series, orchestrating experiments on immune youths to find a cure for the Flare virus.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02ac6b7c81908d44632d6d628339 |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0ed7e8c81909ffed37f5b097188 |
completed | May 3, 2026, 9:41 p.m. |
| NEDg | Description generation | batch_69f7c23410dc8190972245cecfa85871 |
completed | May 3, 2026, 9:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c3031a0c8190ad30d59fe1f2322e |
completed | May 3, 2026, 9:49 p.m. |
Created at: April 9, 2026, 10:13 p.m.