Triple
T3902781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Punjab National Bank |
E90533
|
entity |
| Predicate | numberOfATMs |
P52782
|
FINISHED |
| Object | Over 12000 ATMs (approximate, India-wide) |
—
|
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: Over 12000 ATMs (approximate, India-wide) | Statement: [Punjab National Bank, numberOfATMs, Over 12000 ATMs (approximate, India-wide)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfATMs Context triple: [Punjab National Bank, numberOfATMs, Over 12000 ATMs (approximate, India-wide)]
-
A.
hasATMNetwork
Indicates that an entity operates, participates in, or is connected to a particular automated teller machine (ATM) network for financial transactions.
-
B.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
C.
numberOfTargetInstitutions
Indicates the count of institutions that are designated or identified as targets in a given context or dataset.
-
D.
numberOfFederalReserveBanks
Indicates the quantity of Federal Reserve Banks associated with or relevant to a given entity.
-
E.
numberOfPumps
Indicates the quantity of pumps associated with or required by an entity or system.
- F. None of above. chosen
Provenance (4 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef1aada308190821a3dfa6af170b3 |
completed | March 9, 2026, 4:13 p.m. |
Created at: March 9, 2026, 3:21 p.m.