Triple

T791456
Position Surface form Disambiguated ID Type / Status
Subject Jarawa E16922 entity
Predicate relatedGroup P37 FINISHED
Object Onge E18994 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: Onge | Statement: [Jarawa, relatedGroup, Onge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Onge
Context triple: [Jarawa, relatedGroup, Onge]
  • A. Onge chosen
    The Onge are one of the indigenous Negrito peoples of the Andaman Islands, known for their traditionally nomadic hunter-gatherer lifestyle and critically small population.
  • B. Oni
    Oni is a small town in the Racha region of northwestern Georgia, known for its mountainous surroundings and traditional Georgian architecture.
  • C. Oker
    The Oker is a river in central Germany that flows northward from the Harz Mountains through Lower Saxony before joining the Aller.
  • D. Giewont
    Giewont is a prominent, cross-topped mountain massif in the Polish Tatra Mountains, famed as a national symbol and popular hiking destination overlooking the town of Zakopane.
  • E. Gweru
    Gweru is a central Zimbabwean city that serves as the capital of the Midlands Province and an important commercial and transportation hub.
  • 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_69a4936cb7448190914f5fe4b8d81607 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a798c7608190b9c79c52a1fe0859 completed March 1, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69a67880f9608190b0676eb47ea99ca1 completed March 3, 2026, 5:58 a.m.
Created at: March 1, 2026, 7:38 p.m.