Triple
T81479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bluefield, West Virginia |
E1636
|
entity |
| Predicate | historicalIndustry |
P3008
|
FINISHED |
| Object | bituminous coal |
—
|
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: bituminous coal | Statement: [Bluefield, West Virginia, historicalIndustry, bituminous coal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: historicalIndustry Context triple: [Bluefield, West Virginia, historicalIndustry, bituminous coal]
-
A.
hasHistoricIndustry
chosen
Indicates that an entity has been associated with a notable or historically significant industry or industrial activity in the past.
-
B.
hasIndustrialHeritage
Indicates that an entity possesses or is associated with historically significant industrial sites, structures, or practices.
-
C.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
D.
partOfHistoryOf
Indicates that one entity forms a component, episode, or contributing element within the historical development or narrative of another entity.
-
E.
historicalAssessment
Indicates an evaluation or judgment of something based on its historical context, significance, or development over time.
- 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_69a24c60d19c8190a1b6c105ca59ef5b |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a25053ca208190a371b0d38000c2b9 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb2998c819082681da74601d446 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.