Triple
T15953414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gene Sperling |
E386871
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Allison Abner
Allison Abner is an American television writer and producer known for her work on political and legal dramas.
|
E1207080
|
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: Allison Abner | Statement: [Gene Sperling, spouse, Allison Abner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allison Abner Context triple: [Gene Sperling, spouse, Allison Abner]
-
A.
Allison Abbate
Allison Abbate is an American film producer best known for her work on major animated features such as The Iron Giant, Corpse Bride, and The LEGO Movie.
-
B.
Allison Burnett
Allison Burnett is an American screenwriter and novelist known for his work on films such as "Autumn in New York" and for writing character-driven dramas and thrillers.
-
C.
Catrina Ladd
Catrina Ladd is best known as the wife of late American film producer and studio executive Alan Ladd Jr.
-
D.
Anna Culp
Anna Culp is a television producer best known for her executive production work on the biographical anthology series "Genius."
-
E.
Alana Ladd
Alana Ladd was an American actress and the daughter of film star Alan Ladd, known for appearing in several movies and television productions during the 1950s and 1960s.
- 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: Allison Abner Triple: [Gene Sperling, spouse, Allison Abner]
Generated description
Allison Abner is an American television writer and producer known for her work on political and legal dramas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Allison Abner Target entity description: Allison Abner is an American television writer and producer known for her work on political and legal dramas.
-
A.
Allison Abbate
Allison Abbate is an American film producer best known for her work on major animated features such as The Iron Giant, Corpse Bride, and The LEGO Movie.
-
B.
Allison Burnett
Allison Burnett is an American screenwriter and novelist known for his work on films such as "Autumn in New York" and for writing character-driven dramas and thrillers.
-
C.
Catrina Ladd
Catrina Ladd is best known as the wife of late American film producer and studio executive Alan Ladd Jr.
-
D.
Anna Culp
Anna Culp is a television producer best known for her executive production work on the biographical anthology series "Genius."
-
E.
Alana Ladd
Alana Ladd was an American actress and the daughter of film star Alan Ladd, known for appearing in several movies and television productions during the 1950s and 1960s.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e156f810148190ab4989a0e4a5f8c0 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0025ec39a8819081c0cf996bc59416 |
completed | May 10, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_6a00280686f881909cd2330c018a7e8d |
completed | May 10, 2026, 6:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00285ad1a08190961fdef3f3f991fa |
completed | May 10, 2026, 6:40 a.m. |
Created at: April 10, 2026, 4:53 a.m.