Triple

T6775001
Position Surface form Disambiguated ID Type / Status
Subject Naman E155133 entity
Predicate spokenIn P2266 FINISHED
Object Malakula E153027 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: Malakula | Statement: [Naman, spokenIn, Malakula]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Malakula
Context triple: [Naman, spokenIn, Malakula]
  • A. Malakula chosen
    Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
  • B. Makilala
    Makilala is a municipality in the province of North Cotabato in the Philippines, known for its agricultural economy and proximity to Mount Apo.
  • C. Mabila
    Mabila is the fortified Native American town in present-day Alabama that was the site of a major 1540 battle between Hernando de Soto’s Spanish expedition and the forces of Chief Tuskaloosa.
  • D. Kankia
    Kankia is a town and local government area in northern Nigeria, known for its role as an administrative and commercial center within Katsina State.
  • E. Manfalut
    Manfalut is a city in Upper Egypt known as an agricultural and commercial center within the Asyut region along the Nile.
  • 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d24ddaf08190baffbff991eeb458 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723c67dc08190b21138488c80733a completed March 28, 2026, 12:41 a.m.
Created at: March 27, 2026, 2:13 p.m.