Triple

T15922851
Position Surface form Disambiguated ID Type / Status
Subject Ladies European Tour E386134 entity
Predicate abbreviation P43 FINISHED
Object LET E1143133 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: LET | Statement: [Ladies European Tour, abbreviation, LET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LET
Context triple: [Ladies European Tour, abbreviation, LET]
  • A. LET chosen
    LET is the National Rail station code assigned to Letchworth Garden City railway station in Hertfordshire, England.
  • B. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • C. LeT
    LeT is a Pakistan-based Islamist militant organization widely known for carrying out the 2008 Mumbai terrorist attacks and being designated as a terrorist group by numerous countries.
  • D. LE
    LE is the abbreviation for Les Engagés, a centrist political party in Belgium that emerged from the reform of the former Humanist Democratic Centre (cdH).
  • E. LT
    LT is the abbreviated name for the Logic Theorist, an early computer program that pioneered automated theorem proving in mathematical logic.
  • 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_69d86da686e4819097cbf3b1fc2d881d completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156832a248190bed479bf835a469c completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5aba70c8190a74c45bce6f9b782 completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:52 a.m.