Triple
T8270839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipstick Jungle |
E193422
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Gail Katz |
E300014
|
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: Gail Katz | Statement: [Lipstick Jungle, executiveProducer, Gail Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gail Katz Context triple: [Lipstick Jungle, executiveProducer, Gail Katz]
-
A.
Gail Katz
chosen
Gail Katz is an American film and television producer known for working on major Hollywood projects including the disaster drama "The Perfect Storm."
-
B.
Gloria Katz
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."
-
C.
Gail Berman
Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
-
D.
Pam Katz
Pam Katz is an American screenwriter known for co-writing historical and biographical films, including the 2012 drama "Hannah Arendt."
-
E.
Barbara Siegel
Barbara Siegel is an American author best known for co-writing numerous science fiction and fantasy novels and game-related books, often in collaboration with her husband Scott Siegel.
- 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_69ca82e14ae481908ffdb822cd2192bc |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7986f8cc8190a529dda980dd6e98 |
completed | March 31, 2026, 7:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6e5358888190ad1b5771ca00a097 |
completed | April 3, 2026, 7:37 a.m. |
Created at: March 30, 2026, 5:50 p.m.