Triple

T2998587
Position Surface form Disambiguated ID Type / Status
Subject Dalet E81130 entity
Predicate correspondsToLatinLetter P44428 FINISHED
Object D E183002 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: D | Statement: [Dalet, correspondsToLatinLetter, D]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: D
Context triple: [Dalet, correspondsToLatinLetter, D]
  • A. D chosen
    The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
  • B. D
    D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
  • C. D
    D is the vehicle registration code used on license plates for the German city of Düsseldorf.
  • D. D2
    D2 is a line of the Moscow Central Diameters suburban rail system, providing cross-city commuter rail service through Moscow and its surrounding areas.
  • E. The D
    "The D" is a popular nickname for Detroit, a major U.S. city known for its automotive industry, musical heritage, and role in American industrial history.
  • 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_69ad8b187fc8819085914d3c9ea3142d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9e11c4188190a3ae8fd0cbd8c2c0 completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e468db4819094fb7badbd48ce1e completed March 11, 2026, 8:56 a.m.
Created at: March 8, 2026, 2:59 p.m.