Triple
T17977813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Bloom |
E449520
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Dan Gregor |
—
|
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: Dan Gregor | Statement: [Rachel Bloom, spouse, Dan Gregor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dan Gregor Context triple: [Rachel Bloom, spouse, Dan Gregor]
-
A.
Dan Gregor
chosen
Dan Gregor is an American comedy writer, director, and producer known for his work on television series like "How I Met Your Mother" and films such as "Most Likely to Murder."
-
B.
Guy Gilpatric
Guy Gilpatric was an American aviator, journalist, and author best known for his adventure and aviation-themed fiction, including the story that inspired the film "Action in the North Atlantic."
-
C.
Brady Hepner
Brady Hepner is an American actor best known for his roles in films such as "The Black Phone" and the comedy-drama "The Holdovers."
-
D.
Michael Garvin
Michael Garvin was an American songwriter and producer best known for penning numerous pop and R&B hits, including songs later popularized by major artists like Jennifer Lopez.
-
E.
Mark Andrus
Mark Andrus is an American screenwriter best known for co-writing the acclaimed film "As Good as It Gets."
- 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b200e9108190bcdde5ba7938ba94 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.