Triple

T6771254
Position Surface form Disambiguated ID Type / Status
Subject Anyin language E155046 entity
Predicate languageGroup P3349 FINISHED
Object Tano E302236 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: Tano | Statement: [Anyin language, languageGroup, Tano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tano
Context triple: [Anyin language, languageGroup, Tano]
  • A. Assa River
    The Assa River is a mountain river in the North Caucasus that flows through parts of Georgia and Russia before joining the Terek River.
  • B. Assa River
    The Assa River is a waterway in the North Caucasus region that flows through parts of Russia and Georgia before joining the Sunzha River.
  • C. Central Tano chosen
    Central Tano is a subgroup of the Niger-Congo language family that includes the Akan languages spoken primarily in Ghana and neighboring regions.
  • D. Beni River
    The Beni River is a major waterway in northern Bolivia that flows through the Amazon Basin, supporting rich biodiversity and local communities along its course.
  • E. Bua River
    The Bua River is a major river in Malawi that drains part of the country’s central region before emptying into Lake Malawi.
  • 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_69c6d2496fa08190895d8b625fb0d699 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712c46b70819097401afab991c808 completed March 27, 2026, 11:29 p.m.
Created at: March 27, 2026, 2:13 p.m.