Triple
T15025790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Flaherty |
E378209
|
entity |
| Predicate | hasColleague |
P398
|
FINISHED |
| Object | Carter Heywood |
E699915
|
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: Carter Heywood | Statement: [Mike Flaherty, hasColleague, Carter Heywood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carter Heywood Context triple: [Mike Flaherty, hasColleague, Carter Heywood]
-
A.
Carter Heywood
chosen
Carter Heywood is a witty, openly gay minority affairs liaison in the sitcom "Spin City," known for his sharp humor and social conscience.
-
B.
Carter Hudson
Carter Hudson is an American actor best known for his role as CIA operative Teddy McDonald on the television crime drama series "Snowfall."
-
C.
Carter Horton
Carter Horton is a character from the horror film "Final Destination," known for being one of the high school students who cheats death after a premonition of a catastrophic plane explosion.
-
D.
Carter Verone
Carter Verone is the ruthless Argentine drug lord and primary antagonist in the film "2 Fast 2 Furious."
-
E.
Carter De Haven
Carter De Haven was an American actor, comedian, and film director active in the early to mid-20th century, known for his work in both silent and sound films.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7dfcb508190aec8cd667e27a8ea |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd746008190a7347368ee6d20cf |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:58 a.m.