Triple
T4983430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yamunanagar |
E111942
|
entity |
| Predicate | majorIndustryType |
P53889
|
FINISHED |
| Object | wood-based 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: wood-based industry | Statement: [Yamunanagar, majorIndustryType, wood-based industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorIndustryType Context triple: [Yamunanagar, majorIndustryType, wood-based industry]
-
A.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
B.
majorTradeType
Indicates the primary category or kind of trade activity that characterizes the relationship between the involved entities.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
industrialCategory
chosen
Indicates the industry or sector classification to which an entity (such as a business or organization) belongs.
- 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_69bd441adc208190b70a033a0741d01e |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.