Triple

T8651735
Position Surface form Disambiguated ID Type / Status
Subject Tebu languages E205114 entity
Predicate hasAlternativeName P39 FINISHED
Object Tebuic E6206 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: Tebuic | Statement: [Tebu languages, hasAlternativeName, Tebuic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tebuic
Context triple: [Tebu languages, hasAlternativeName, Tebuic]
  • A. Tebuange
    Tebuange is a small village settlement located on the island of Nonouti in Kiribati, likely characterized by a traditional Pacific island community and subsistence lifestyle.
  • B. Tebu chosen
    Tebu is a Saharan ethnic group and language community primarily inhabiting parts of southern Libya, Chad, and Niger.
  • C. Tahkuna
    Tahkuna is a coastal settlement in northern Estonia, located on Hiiumaa Island and known for its proximity to the historic Tahkuna Lighthouse.
  • D. Yambu
    Yambu is a coastal city in western Saudi Arabia on the Red Sea, known as an important port and industrial center.
  • E. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • 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_69ca834e56848190abb0eeaec9dedd32 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc484051b48190b1d0cc63426c204d completed March 31, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ceccc95b588190b5e44c73cf93d18b completed April 2, 2026, 8:08 p.m.
Created at: March 30, 2026, 6:29 p.m.