Triple

T10807393
Position Surface form Disambiguated ID Type / Status
Subject INSA E255003 entity
Predicate abbreviation P43 FINISHED
Object INSA E255003 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: INSA | Statement: [INSA, abbreviation, INSA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: INSA
Context triple: [INSA, abbreviation, INSA]
  • A. INSA chosen
    INSA is India’s premier national academy dedicated to promoting excellence in science and representing the country’s scientific community at national and international levels.
  • B. INSU
    INSU is a French national research organization that manages scientific infrastructure and services, particularly in the fields of Earth and environmental sciences.
  • C. INNSA
    INNSA is the UN/LOCODE identifier for Jawaharlal Nehru Port, a major container port near Mumbai, India.
  • D. INSA Rouen Normandie
    INSA Rouen Normandie is a French grande école of engineering that offers multidisciplinary engineering education and research programs as part of the national INSA network.
  • E. INSA Rennes
    INSA Rennes is a leading French public engineering school located in Rennes, specializing in science and technology education and research.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733b506488190921e6a1f4168dd9e completed April 9, 2026, 5:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69de8513fe0881909d6833c85aac03a8 completed April 14, 2026, 6:19 p.m.
Created at: April 8, 2026, 9:18 p.m.