Triple
T4656671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bergen-Lafayette |
E102425
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Greenville |
E105109
|
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: Greenville | Statement: [Bergen-Lafayette, adjacentTo, Greenville]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Greenville Context triple: [Bergen-Lafayette, adjacentTo, Greenville]
-
A.
Greenville
chosen
Greenville is a residential neighborhood in the southern part of Jersey City, New Jersey, known for its diverse community and urban character.
-
B.
Greenville
Greenville is a small city in south-central Alabama known for its historic downtown and role as the county seat of Butler County.
-
C.
Greenville
Greenville is a village and census-designated place in the town of Smithfield in Providence County, Rhode Island, known for its suburban character and historic New England charm.
-
D.
Greenville
Greenville is a small New England town in southern New Hampshire known for its historic mill village character and riverside setting.
-
E.
Greenville, South Carolina
Greenville, South Carolina is a rapidly growing city in the northwestern part of the state, known for its revitalized downtown, thriving manufacturing and technology sectors, and proximity to the Blue Ridge Mountains.
- 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_69bd43d823288190952279faa0d1d066 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd63193a108190a7d9aec1d1d40cf8 |
completed | March 20, 2026, 3:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfaf28c148190b46cf846528034c5 |
completed | March 21, 2026, 1:57 a.m. |
Created at: March 20, 2026, 1:14 p.m.