Triple

T13937881
Position Surface form Disambiguated ID Type / Status
Subject Munchi E335165 entity
Predicate hasISO6393Code P8719 FINISHED
Object tiv E321208 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: tiv | Statement: [Munchi, hasISO6393Code, tiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: tiv
Context triple: [Munchi, hasISO6393Code, tiv]
  • A. Tiv chosen
    The Tiv are an ethnic group primarily found in central Nigeria, known for their rich agricultural traditions, distinctive language, and vibrant cultural festivals.
  • B. TIT
    TIT is a leading Japanese national research university in Tokyo renowned for its strong programs in science, engineering, and technology.
  • C. Ti
    Ti was an ancient Egyptian official of the Fifth Dynasty, known from his elaborately decorated mastaba tomb at Saqqara that provides important insights into Old Kingdom life and art.
  • D. tj
    tj is the GitHub username of TJ Holowaychuk, a prolific open-source developer known for creating popular Node.js and Go tools and frameworks.
  • E. tet
    tet is the ISO 639-1 language code for Tetum, an Austronesian language spoken primarily in East Timor.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2cf5cc8c8190bea74291702b2925 completed April 14, 2026, 12:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce89d2348190b5a50376c2b8248c completed May 3, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:17 p.m.