Triple
T6148884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Triangle region of North Carolina |
E137146
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Garner |
E5231
|
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: Garner | Statement: [Triangle region of North Carolina, hasMajorCity, Garner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garner Context triple: [Triangle region of North Carolina, hasMajorCity, Garner]
-
A.
Garner
chosen
Garner is a surname most notably associated with John Nance Garner, the 32nd vice president of the United States under Franklin D. Roosevelt.
-
B.
Coker
Coker is a residential and commercial neighborhood located within the Surulere area of Lagos, Nigeria.
-
C.
Garner Ted Armstrong
Garner Ted Armstrong was an American televangelist and religious broadcaster known for his influential role in the Worldwide Church of God and later for founding the Church of God International.
-
D.
Eldridge
Eldridge is an English-language surname of Old English origin, borne by various notable individuals across fields such as politics, the arts, and sports.
-
E.
Grier
Grier is the surname of Pam Grier, an influential American actress renowned for her groundbreaking roles in 1970s blaxploitation 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05ce21820819096be9159d6b70a5f |
completed | March 22, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c13608944481909e22df6131a06e41 |
completed | March 23, 2026, 12:46 p.m. |
Created at: March 22, 2026, 4:16 p.m.