Triple
T16611592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crashing |
E403581
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Lara Spotts
Lara Spotts is a television producer best known for her work on the HBO comedy series "Crashing."
|
E1247311
|
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: Lara Spotts | Statement: [Crashing, producer, Lara Spotts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lara Spotts Context triple: [Crashing, producer, Lara Spotts]
-
A.
Lara Stone
Lara Stone is a Dutch fashion model renowned for her distinctive gap-toothed look and work with major luxury brands and magazines.
-
B.
Lara Breay
Lara Breay is a film producer best known for her work on the animated superhero comedy "Megamind."
-
C.
Lyla Garrity
Lyla Garrity is a central character on the television series "Friday Night Lights," known as a popular cheerleader whose personal struggles and evolving relationships drive much of the show's emotional drama.
-
D.
Lara Worthington
Lara Worthington is an Australian model and media personality best known for her work in fashion campaigns and reality television, as well as her high-profile public image.
-
E.
Layla Maloney
Layla Maloney is a character in the comedy film "Big Daddy," where she becomes the romantic partner of Adam Sandler’s character, Sonny Koufax.
- 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: Lara Spotts Triple: [Crashing, producer, Lara Spotts]
Generated description
Lara Spotts is a television producer best known for her work on the HBO comedy series "Crashing."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lara Spotts Target entity description: Lara Spotts is a television producer best known for her work on the HBO comedy series "Crashing."
-
A.
Lara Stone
Lara Stone is a Dutch fashion model renowned for her distinctive gap-toothed look and work with major luxury brands and magazines.
-
B.
Lara Breay
Lara Breay is a film producer best known for her work on the animated superhero comedy "Megamind."
-
C.
Lyla Garrity
Lyla Garrity is a central character on the television series "Friday Night Lights," known as a popular cheerleader whose personal struggles and evolving relationships drive much of the show's emotional drama.
-
D.
Lara Worthington
Lara Worthington is an Australian model and media personality best known for her work in fashion campaigns and reality television, as well as her high-profile public image.
-
E.
Layla Maloney
Layla Maloney is a character in the comedy film "Big Daddy," where she becomes the romantic partner of Adam Sandler’s character, Sonny Koufax.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e36096356c819092815d64db041793 |
completed | April 18, 2026, 10:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0123257b908190819986393cb35748 |
completed | May 11, 2026, 12:30 a.m. |
| NEDg | Description generation | batch_6a012433d4e08190a0e0cb9c82105340 |
completed | May 11, 2026, 12:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01248b53d88190a4ec4fa6cee89bb1 |
completed | May 11, 2026, 12:36 a.m. |
Created at: April 10, 2026, 5:17 a.m.