Triple
T3237191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Tale |
E67882
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Jennifer Fox |
E340336
|
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: Jennifer Fox | Statement: [The Tale, screenwriter, Jennifer Fox]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jennifer Fox Context triple: [The Tale, screenwriter, Jennifer Fox]
-
A.
Jennifer Fox
Jennifer Fox is an American film and television producer known for her work on acclaimed projects such as the geopolitical thriller "Syriana."
-
B.
Jennifer Fox
chosen
Jennifer Fox is an American filmmaker and producer known for her autobiographical drama film "The Tale" and her work in documentary cinema.
-
C.
Laura Poitras
Laura Poitras is an American documentary filmmaker and journalist best known for her work on U.S. surveillance and national security, including the Oscar-winning film "Citizenfour" about Edward Snowden.
-
D.
Jane Kurson
Jane Kurson is a film editor best known for her work on the 1988 fantasy-comedy film "Beetlejuice."
-
E.
Ari Wegner
Ari Wegner is an acclaimed Australian cinematographer known for her visually striking work on films such as "The Power of the Dog."
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaef29bf48190a9aa3a39f0138428 |
completed | March 8, 2026, 5:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e82b6bfc8190a6db566c37ef2eff |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:08 p.m.