Triple

T675666
Position Surface form Disambiguated ID Type / Status
Subject Orly 4 E13071 entity
Predicate hasIATAAirportCode P2569 FINISHED
Object ORY E10907 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: ORY | Statement: [Orly 4, hasIATAAirportCode, ORY]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ORY
Context triple: [Orly 4, hasIATAAirportCode, ORY]
  • A. ORY chosen
    ORY is the three-letter IATA airport code for Paris Orly Airport, a major international airport serving the Paris metropolitan area in France.
  • B. OR
    OR is the official two-letter United States Postal Service abbreviation for the state of Oregon.
  • C. WR
    WR is the abbreviation for the German Council of Science and Humanities, a key advisory body that counsels the German federal and state governments on science, research, and higher education policy.
  • D. RE
    RE is the common abbreviation for the British Army’s Corps of Royal Engineers, responsible for military engineering and technical support.
  • E. REN
    REN is a blockchain-based project and protocol focused on enabling cross-chain liquidity and interoperability between different cryptocurrency networks.
  • 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_69a4933d3bf88190972041cd8cf143b9 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a0266e7c8190a94c4b4b761c59f4 completed March 1, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5dc9f5f7c8190a766c6b545d1abd8 completed March 2, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:36 p.m.