Triple
T10393258
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steps |
E244941
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Faye Tozer
Faye Tozer is an English singer, dancer, and actress best known as a member of the pop group Steps.
|
E879317
|
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: Faye Tozer | Statement: [Steps, hasMember, Faye Tozer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faye Tozer Context triple: [Steps, hasMember, Faye Tozer]
-
A.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
B.
Faye Emerson
Faye Emerson was an American film and stage actress who became a popular early television personality in the 1940s and 1950s.
-
C.
Annette Kirk
Annette Kirk is an American cultural advocate and widow of conservative thinker Russell Kirk, known for promoting his intellectual legacy and traditionalist ideas through institutions such as the Kirk Center for Cultural Renewal.
-
D.
Diane Lester
Diane Lester is a key character in the financial thriller film "Money Monster," serving as a corporate communications chief entangled in the unfolding live-broadcast crisis.
-
E.
Fay Holden
Fay Holden was a British-born American actress best known for playing Mrs. Emily Hardy, the mother in the popular Andy Hardy film series of the 1930s and 1940s.
- 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: Faye Tozer Triple: [Steps, hasMember, Faye Tozer]
Generated description
Faye Tozer is an English singer, dancer, and actress best known as a member of the pop group Steps.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Faye Tozer Target entity description: Faye Tozer is an English singer, dancer, and actress best known as a member of the pop group Steps.
-
A.
Faye Medwick
Faye Medwick is a fictional character appearing in the work titled "Chapter Two."
-
B.
Faye Emerson
Faye Emerson was an American film and stage actress who became a popular early television personality in the 1940s and 1950s.
-
C.
Annette Kirk
Annette Kirk is an American cultural advocate and widow of conservative thinker Russell Kirk, known for promoting his intellectual legacy and traditionalist ideas through institutions such as the Kirk Center for Cultural Renewal.
-
D.
Diane Lester
Diane Lester is a key character in the financial thriller film "Money Monster," serving as a corporate communications chief entangled in the unfolding live-broadcast crisis.
-
E.
Fay Holden
Fay Holden was a British-born American actress best known for playing Mrs. Emily Hardy, the mother in the popular Andy Hardy film series of the 1930s and 1940s.
- 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_69d381b5116081908d85227bab6d3c0c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9b6c750819087678bf81a3ef806 |
completed | April 7, 2026, 11:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9881d84588190a9117064a0950ac1 |
completed | April 10, 2026, 11:30 p.m. |
| NEDg | Description generation | batch_69d98ae8403c81908a229aa06bd0388a |
completed | April 10, 2026, 11:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d98ce9ba0c8190a7c62fa670e23705 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 6, 2026, 12:06 p.m.