Triple
T6734848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narsinghpur |
E153726
|
entity |
| Predicate | hasBankingFacilities |
P525
|
FINISHED |
| Object | nationalized banks branches |
—
|
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: nationalized banks branches | Statement: [Narsinghpur, hasBankingFacilities, nationalized banks branches]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBankingFacilities Context triple: [Narsinghpur, hasBankingFacilities, nationalized banks branches]
-
A.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
-
B.
hasFinancialInstitution
chosen
Indicates that one entity is associated with or linked to a financial institution, such as a bank or similar financial service provider.
-
C.
hasATMNetwork
Indicates that an entity operates, participates in, or is connected to a particular automated teller machine (ATM) network for financial transactions.
-
D.
hasBankType
Indicates that an entity is associated with or classified by a particular type or category of bank.
-
E.
hasBankingOnApron
Indicates that an entity (such as a structure or platform) has a banking or sloped edge feature present on its apron area.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d16ecbe08190b019d547f631a725 |
completed | March 27, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69c6d09067a0819087ed6c820f4699f8 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.