Triple
T5272433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trident Technical College |
E119290
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Charleston |
E13422
|
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: Charleston | Statement: [Trident Technical College, city, Charleston]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charleston Context triple: [Trident Technical College, city, Charleston]
-
A.
Charleston
Charleston is a historic waterfront neighborhood in Bremerton, Washington, known for its residential character and proximity to the Puget Sound naval facilities.
-
B.
Charleston
Charleston is a small city in east-central Illinois best known as the home of Eastern Illinois University.
-
C.
Charleston
Charleston was the original name of the city now known as Lorain, Ohio, a Great Lakes industrial community on the shores of Lake Erie.
-
D.
Charleston
chosen
Charleston is a historic port city in South Carolina known as a key center of colonial resistance to British rule, including major protests against imperial taxation.
-
E.
Charlotte
Charlotte is a royal figure bearing the traditional title of Princess Royal, historically associated with the eldest daughter of the British monarch.
- 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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7c2145908190a59570875d5bf3d9 |
completed | March 20, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf06ced8f481909d1714ed3415ab85 |
completed | March 21, 2026, 8:59 p.m. |
Created at: March 20, 2026, 1:51 p.m.