Triple
T35480243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pantnagar |
E1025450
|
entity |
| Predicate | hasIndustrialUnitsFrom |
P20603
|
FINISHED |
| Object | automobile sector |
—
|
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: automobile sector | Statement: [Pantnagar, hasIndustrialUnitsFrom, automobile sector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialUnitsFrom Context triple: [Pantnagar, hasIndustrialUnitsFrom, automobile sector]
-
A.
hasIndustrialPlant
Indicates that an entity possesses, operates, or is associated with an industrial plant facility.
-
B.
hasIndustrialSiteIn
Indicates that an entity possesses, operates, or is responsible for an industrial facility located within a specified place or area.
-
C.
hasIndustrialCompany
Indicates that one entity possesses, controls, or is associated with an industrial company.
-
D.
hasProductionFacilitiesIn
Indicates that an entity operates or owns production facilities located within a specified geographic area or jurisdiction.
-
E.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
- 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a00694f72888190983fee7d687a6daa |
completed | May 10, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_6a00685dbf44819098ea0c86bb9e50d8 |
completed | May 10, 2026, 11:13 a.m. |
Created at: May 3, 2026, 4:04 p.m.