Triple

T13579662
Position Surface form Disambiguated ID Type / Status
Subject ODTÜ E324378 entity
Predicate shortName P43 FINISHED
Object ODTÜ E324378 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: ODTÜ | Statement: [ODTÜ, shortName, ODTÜ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ODTÜ
Context triple: [ODTÜ, shortName, ODTÜ]
  • A. ODTÜ chosen
    ODTÜ is a leading public research university in Ankara, Turkey, renowned for its strong engineering, natural sciences, and social sciences programs.
  • B. Bilkent University
    Bilkent University is a leading private research university in Ankara, Turkey, known for its strong emphasis on science, engineering, and international education.
  • C. Hacettepe University
    Hacettepe University is a major public research university in Turkey, renowned for its strong programs in medicine, science, and engineering.
  • D. Ankara University
    Ankara University is a major public research university in Turkey’s capital city, known for its wide range of academic programs and significant role in the country’s higher education and public service.
  • E. Kadir Has University
    Kadir Has University is a private foundation university in Istanbul, Turkey, known for its focus on research, innovation, and contemporary academic programs.
  • 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_69d80769100c819099111274614f5ed2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb03052088190a2b68c106059828e completed April 12, 2026, 2:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76bbdb2d0819089f094e57dde28cf completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:48 p.m.