Triple
T7862231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rishra |
E182526
|
entity |
| Predicate | hasIndustrialType |
P20603
|
FINISHED |
| Object | jute 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: jute industry | Statement: [Rishra, hasIndustrialType, jute industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialType Context triple: [Rishra, hasIndustrialType, jute industry]
-
A.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
B.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
-
C.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
D.
hasIndustrialTown
Indicates that an entity possesses or is associated with a town characterized primarily by industrial activities or facilities.
-
E.
industrialCategory
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_69ca82887fd48190975896bf38c4596b |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb36be5f408190b82a097b0825c57a |
completed | March 31, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69cae925ca388190ae4a01fa76e957e8 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:53 p.m.