Triple
T11263144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bell Gardens |
E266614
|
entity |
| Predicate | isLocatedNear |
P350
|
FINISHED |
| Object | Commerce |
E266615
|
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: Commerce | Statement: [Bell Gardens, isLocatedNear, Commerce]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Commerce Context triple: [Bell Gardens, isLocatedNear, Commerce]
-
A.
Commerce
chosen
Commerce is a city in Los Angeles County, California, known for its industrial base, rail yards, and large outlet shopping center.
-
B.
Commerce
Commerce is a small city in northeast Texas known for hosting Texas A&M University–Commerce and functioning as part of the greater Dallas–Fort Worth region.
-
C.
Commerce
Commerce is a Paris Métro station located in the 15th arrondissement, serving the surrounding residential and commercial neighborhood.
-
D.
Commerce and Trade
Commerce and Trade refers to the body of U.S. federal law and policy governing business activities, markets, and economic transactions, as codified in Title 15 of the United States Code.
-
E.
Commercy
Commercy is a small town in northeastern France best known for its madeleine pastries and its role as an administrative center in the Meuse department.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94d56048190bf808e1bc2188714 |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4ccba233481909f00ebe2237c4f0c |
completed | April 19, 2026, 12:38 p.m. |
Created at: April 8, 2026, 9:31 p.m.