Triple
T22098435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peace College |
E546100
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Raleigh |
—
|
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: Raleigh | Statement: [Peace College, city, Raleigh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raleigh Context triple: [Peace College, city, Raleigh]
-
A.
Raleigh
Raleigh is the nickname of Henry "Raleigh" Gordon, likely used as his familiar or professional moniker.
-
B.
Raleigh
chosen
Raleigh is the capital city of North Carolina and a major hub for education, technology, and research within the state’s Research Triangle region.
-
C.
Raleigh
Raleigh is a small town located in Raleigh County, West Virginia, known primarily as a local residential and community center within the county.
-
D.
Raleigh
Raleigh is a small rural locality in the Mid North Coast region of New South Wales, Australia, known for its agricultural surroundings and proximity to the Bellinger River.
-
E.
Greensboro
Greensboro is a small rural town in Vermont known for its scenic lakes, agricultural landscape, and arts-oriented summer community.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129131b4c8190b443bc820d9b5c61 |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.