Triple
T21536718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crossing Over |
E531367
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Gregory Goodell |
—
|
NE NERFINISHED |
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: Gregory Goodell | Statement: [Crossing Over, producer, Gregory Goodell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gregory Goodell Context triple: [Crossing Over, producer, Gregory Goodell]
-
A.
Gregory Goodell
chosen
Gregory Goodell is a film producer best known for his work on the crime thriller "Deep Cover."
-
B.
Mark Daboll
Mark Daboll is a member of the Daboll family, related to NFL head coach Brian Daboll.
-
C.
Gregory J. Harbaugh
Gregory J. Harbaugh is a former NASA astronaut and engineer who flew on multiple Space Shuttle missions and conducted spacewalks to service the Hubble Space Telescope.
-
D.
John Tusa
John Tusa is a British arts administrator, broadcaster, and former managing director of the BBC World Service and the Barbican Centre.
-
E.
Daniel Connelly
Daniel Connelly is a central character in Cecelia Ahern's novel "P.S. I Love You," serving as a key figure in Holly Kennedy's emotional journey after her husband's death.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0e5a9c8190894ec3666d3296aa |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.