Triple

T22666760
Position Surface form Disambiguated ID Type / Status
Subject ocamlopt E559811 entity
Predicate maintainedBy P86 FINISHED
Object Inria E265286 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: Inria | Statement: [ocamlopt, maintainedBy, Inria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inria
Context triple: [ocamlopt, maintainedBy, Inria]
  • A. INRIA chosen
    INRIA is the French national research institute dedicated to computer science and applied mathematics, known for its leading contributions to digital science and technology.
  • B. Laboratoire Ampère
    Laboratoire Ampère is a French research laboratory associated with INSA Lyon that focuses on electrical engineering, automation, and related applied sciences.
  • C. LORIA
    LORIA is a French research laboratory specializing in computer science and information technologies, jointly operated by several institutions in the Lorraine region.
  • D. Laboratoire de Recherche en Informatique
    Laboratoire de Recherche en Informatique is a French computer science research laboratory known for its work in theoretical computer science, formal methods, and related areas.
  • E. Lyon research center
    The Lyon research center is a major French Petroleum Institute facility specializing in research and development in petroleum, energy, and related technologies.
  • 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_69e2454a158c819093b8e35f5045efb6 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1781c2c808190baf6964ca1eced6f completed April 29, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b73e7aff48190a2357f66abe29938 completed May 18, 2026, 8:17 p.m.
Created at: April 17, 2026, 3:09 p.m.