Triple
T9969766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan in Real Life |
E196174
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Peter Hedges |
E276002
|
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: Peter Hedges | Statement: [Dan in Real Life, writer, Peter Hedges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Hedges Context triple: [Dan in Real Life, writer, Peter Hedges]
-
A.
Peter Hedges
chosen
Peter Hedges is an American novelist, playwright, and filmmaker best known for writing the novel and screenplay for "What's Eating Gilbert Grape" and directing films such as "Pieces of April" and "Dan in Real Life."
-
B.
Sacha Gervasi
Sacha Gervasi is a British screenwriter and director known for films such as "The Terminal" and the documentary "Anvil! The Story of Anvil."
-
C.
Dan Gilroy
Dan Gilroy is an American screenwriter and director best known for writing and directing the critically acclaimed film "Nightcrawler."
-
D.
Dan Goor
Dan Goor is an American television writer and producer best known for co-creating the comedy series "Brooklyn Nine-Nine" and his work on shows like "Parks and Recreation."
-
E.
Michael Arndt
Michael Arndt is an Academy Award–winning American screenwriter known for acclaimed films such as Little Miss Sunshine and Toy Story 3.
- 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_69ca82eea2b88190a0e511d21a31f386 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb7b7ea9881908a56f11e2e446dd0 |
completed | April 2, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d257c002cc8190becc9730b2c01782 |
completed | April 5, 2026, 12:38 p.m. |
Created at: March 30, 2026, 8:48 p.m.