Triple
T10481540
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kim Carter |
E247180
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Carter |
E93561
|
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 | Statement: [Kim Carter, familyName, Carter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carter Context triple: [Kim Carter, familyName, Carter]
-
A.
Carter
"Carter" is a Canadian crime-comedy television series starring Jerry O’Connell as a Hollywood actor who returns to his hometown and begins solving real-life crimes.
-
B.
Carter
chosen
Carter is a common English surname borne by numerous notable individuals, including the 39th U.S. president, Jimmy Carter.
-
C.
Carter
Carter is a fictional character from the action-adventure film "Soldiers of Fortune."
-
D.
Carter Verone
Carter Verone is the ruthless Argentine drug lord and primary antagonist in the film "2 Fast 2 Furious."
-
E.
Carter Heywood
Carter Heywood is a witty, openly gay minority affairs liaison in the sitcom "Spin City," known for his sharp humor and social conscience.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5095c5dc88190902582db28df01b4 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90db8b1288190bb6bb064cb0724e0 |
completed | April 10, 2026, 2:48 p.m. |
Created at: April 6, 2026, 12:22 p.m.