Triple

T13901592
Position Surface form Disambiguated ID Type / Status
Subject Mata Khivi E334234 entity
Predicate honorificPrefix P536 FINISHED
Object Mata E100841 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: Mata | Statement: [Mata Khivi, honorificPrefix, Mata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mata
Context triple: [Mata Khivi, honorificPrefix, Mata]
  • A. Mata chosen
    Mata is a title used in certain South Asian cultural and religious contexts, often signifying a revered mother figure or goddess.
  • B. Mazani
    Mazani is an alternative name for the Mazanderani language, an Iranian language spoken primarily along the southern coast of the Caspian Sea in northern Iran.
  • C. Matta
    Matta is a surname most prominently associated with Thad Matta, a successful American college basketball coach known for his tenures at Xavier and Ohio State.
  • D. Matta
    Matta is a town located in Pakistan’s Swat District, known for its agricultural surroundings and scenic mountainous landscape.
  • E. Mambae
    Mambae is an Austronesian language spoken primarily in the central and eastern regions of Timor-Leste.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de25d9c7a48190ad8fb0ca676f4f7b completed April 14, 2026, 11:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c722e72081909090b2d64000ebd9 completed May 3, 2026, 10:07 p.m.
Created at: April 9, 2026, 10:15 p.m.