Triple

T14606995
Position Surface form Disambiguated ID Type / Status
Subject Ambrolauri Airport E342855 entity
Predicate hasCode P9567 FINISHED
Object UGAM E342855 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: UGAM | Statement: [Ambrolauri Airport, hasCode, UGAM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UGAM
Context triple: [Ambrolauri Airport, hasCode, UGAM]
  • A. UGAM chosen
    UGAM is the ICAO airport code for Ambrolauri Airport, a regional airport serving the town of Ambrolauri in Georgia.
  • B. UGM
    UGM is a leading public research university in Yogyakarta, Indonesia, renowned as one of the country’s oldest and most prestigious institutions of higher education.
  • C. Universitas Pekalongan
    Universitas Pekalongan is a higher education institution located in the coastal city of Pekalongan on the island of Java, Indonesia.
  • D. University of Jember
    The University of Jember is a public higher education institution located in Jember, East Java, Indonesia, offering a wide range of academic programs and research activities.
  • E. Andalas University
    Andalas University is one of Indonesia’s oldest and leading public universities, located in Padang, West Sumatra, and known for its wide range of academic programs and research contributions.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb44d327c8190a8d20568429d0f80 completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda91d05e48190ac945e381d6d5dd9 completed May 8, 2026, 9:13 a.m.
Created at: April 10, 2026, 1:25 a.m.