Triple

T7019415
Position Surface form Disambiguated ID Type / Status
Subject Precision Air E162779 entity
Predicate cityServed P82 FINISHED
Object Tabora E180266 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: Tabora | Statement: [Precision Air, cityServed, Tabora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tabora
Context triple: [Precision Air, cityServed, Tabora]
  • A. Tabora chosen
    Tabora is a historic town in western Tanzania known as a regional trade center and former hub of 19th-century caravan routes.
  • B. Bosambo
    Bosambo is a prominent fictional African chief featured in Edgar Wallace’s "Sanders of the River" stories, known for his cunning, charisma, and complex relationship with colonial authority.
  • C. Massinga
    Massinga is a coastal town in southern Mozambique that serves as an important local center within Inhambane Province.
  • D. Kasindi
    Kasindi is a border town in eastern Democratic Republic of the Congo, located near Uganda and serving as an important regional trade and transport hub.
  • E. Atambua
    Atambua is a town in East Nusa Tenggara, Indonesia, located near the border with Timor-Leste and serving as an important regional trade and transit center.
  • 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e1e8e36c81908c95a8181781cda4 completed March 27, 2026, 8 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7ad743c2c819081d7b8cda5720ba3 completed March 28, 2026, 10:29 a.m.
Created at: March 27, 2026, 2:34 p.m.