Triple

T12564349
Position Surface form Disambiguated ID Type / Status
Subject BOCHK E295427 entity
Predicate hasServiceChannel P44485 FINISHED
Object ATMs E662819 NE 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: ATMs | Statement: [BOCHK, hasServiceChannel, ATMs]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ATMs
Context triple: [BOCHK, hasServiceChannel, ATMs]
  • A. ATMs chosen
    ATMs (Automated Teller Machines) are self-service banking terminals that allow customers to perform financial transactions such as cash withdrawals, deposits, and balance inquiries without the need for a human teller.
  • B. ATM
    ATM is the commonly used abbreviation for the Autoritat del Transport Metropolità, the public authority that coordinates and manages metropolitan public transport in the Barcelona area.
  • C. ATM
    "ATM" is a hit single by rapper J. Cole known for its commentary on materialism and catchy "count it up" refrain.
  • D. ATM
    The ATM is the unified military organization responsible for the defense and security of Malaysia.
  • E. ATM
    ATM is the commonly used abbreviation for Atlético de Madrid, the Spanish professional football club nicknamed "Los Colchoneros."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d95494ae1c81908b9ee14b8ef92a65 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6558f87b081909ba179b49bae3913 completed May 2, 2026, 7:50 p.m.
Created at: April 8, 2026, 11:49 p.m.