Triple
T4486921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snake Alley |
E107262
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Burlington |
E158535
|
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: Burlington | Statement: [Snake Alley, city, Burlington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burlington Context triple: [Snake Alley, city, Burlington]
-
A.
Burlington
Burlington is a suburban town in Massachusetts known for its proximity to Boston and its mix of residential neighborhoods, office parks, and retail centers.
-
B.
Burlington
Burlington is a historic city in present-day New Jersey that once served as the colonial capital of the Province of New Jersey.
-
C.
Burlington
Burlington is a mid-sized city in southern Ontario, Canada, located on the shores of Lake Ontario between Toronto and Hamilton.
-
D.
Burlington
chosen
Burlington is a city in North Carolina known historically as a railroad and textile manufacturing hub in the Piedmont region of the state.
-
E.
Burlington
Burlington is a small city in northwestern Washington State known as a commercial hub for the surrounding Skagit Valley region.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd52a958288190974b292f54a0e045 |
completed | March 20, 2026, 1:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd37f7ed48190ae0a82597aafc66e |
completed | March 20, 2026, 11:08 p.m. |
Created at: March 20, 2026, 12:59 p.m.