Triple
T10255377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Willard Huyck |
E240448
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | Gloria Katz |
E213748
|
NE FINISHED |
How this triple was built (2 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: Gloria Katz | Statement: [Willard Huyck, collaboratedWith, Gloria Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gloria Katz Context triple: [Willard Huyck, collaboratedWith, Gloria Katz]
-
A.
Gloria Katz
chosen
Gloria Katz was an American screenwriter and producer best known for her collaborations with George Lucas, including work on films like "American Graffiti" and "Star Wars."
-
B.
Gail Katz
Gail Katz is an American film and television producer known for working on major Hollywood projects including the disaster drama "The Perfect Storm."
-
C.
Janet Margolin
Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
-
D.
Nancy Goodman
Nancy Goodman is an American diplomat, businesswoman, and philanthropist best known for founding the Susan G. Komen Breast Cancer Foundation.
-
E.
Judy Levitt
Judy Levitt is an American actress best known for her long marriage to Star Trek actor Walter Koenig and for appearing in several of his film and television projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24c69ac81908b4da53d13407ac8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d979d64a5481909be6d6bd1d8b6433 |
completed | April 10, 2026, 10:29 p.m. |
Created at: April 6, 2026, 11:30 a.m.