Triple

T27719220
Position Surface form Disambiguated ID Type / Status
Subject Rohini Sector 18, 19 E698904 entity
Predicate hasATM P52782 FINISHED
Object yes 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: yes | Statement: [Rohini Sector 18, 19, hasATM, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasATM
Context triple: [Rohini Sector 18, 19, hasATM, yes]
  • A. hasATMNetwork
    Indicates that an entity operates, participates in, or is connected to a particular automated teller machine (ATM) network for financial transactions.
  • B. hasBankOn
    Indicates that one entity is located on or alongside the bank (edge) of another entity, typically a river, lake, or similar body.
  • C. numberOfATMs chosen
    Indicates the quantitative relationship specifying how many ATMs are associated with a given entity or location.
  • D. hasBank
    Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
  • E. hasBanking
    Indicates that one entity provides or is associated with banking services or facilities for another entity.
  • 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_69ef591012dc8190a6f1ec994f9f7ff7 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6363a71e88190a2df9d30f527154d completed May 2, 2026, 5:36 p.m.
PD Predicate disambiguation batch_69f63188e7408190af8ce8b93d128c63 completed May 2, 2026, 5:16 p.m.
Created at: April 27, 2026, 3:06 p.m.