Triple
T115301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombay Presidency |
E2324
|
entity |
| Predicate | significantIndustry |
P71
|
FINISHED |
| Object | textile industry |
—
|
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: textile industry | Statement: [Bombay Presidency, significantIndustry, textile industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantIndustry Context triple: [Bombay Presidency, significantIndustry, textile industry]
-
A.
isMajorIndustrialEconomy
Indicates that an entity is one of the world’s leading industrialized economies, characterized by large-scale industrial output and significant influence in global economic activity.
-
B.
sector
chosen
Indicates that an entity operates in, belongs to, or is associated with a particular economic or industrial sector.
-
C.
economicClassification
Indicates how an entity is categorized based on its economic characteristics, status, or role within an economic system.
-
D.
isIndustrialCenter
Indicates that a place functions as a major hub of industrial activity, production, or manufacturing within a region.
-
E.
significance
Indicates that one entity holds particular importance, influence, or meaningful impact in relation to another entity or context.
- 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_69a2506c5428819085c28a8884790e29 |
completed | Feb. 28, 2026, 2:18 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:24 a.m.