Triple
T4796039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooks Locomotive Works |
E106712
|
entity |
| Predicate | cityEconomicRole |
P2223
|
FINISHED |
| Object | major employer in Dunkirk, New York |
—
|
LITERAL 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: major employer in Dunkirk, New York | Statement: [Brooks Locomotive Works, cityEconomicRole, major employer in Dunkirk, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityEconomicRole Context triple: [Brooks Locomotive Works, cityEconomicRole, major employer in Dunkirk, New York]
-
A.
urbanRole
Indicates the function, status, or role that an entity holds within an urban or city context.
-
B.
hasEconomicRole
chosen
Indicates that an entity participates in or fulfills a specific function, position, or responsibility within an economic system or activity.
-
C.
isEconomicCenter
Indicates that an entity functions as a primary hub for economic activity, such as trade, finance, or industry, within a region or system.
-
D.
regionalEconomyType
Indicates the type or classification of an economy associated with a specific region.
-
E.
hasMajorCityRole
Indicates that an entity plays a significant official or functional role in the governance, administration, or key operations of a major city.
- F. None of above.
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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6b40c29c8190adab3503f8ba0145 |
completed | March 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69bd622f88188190a51d52ccfad3d2dd |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:22 p.m.