Triple

T4147042
Position Surface form Disambiguated ID Type / Status
Subject Jayabaya E89809 entity
Predicate capital P234 FINISHED
Object Daha E88314 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: Daha | Statement: [Jayabaya, capital, Daha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daha
Context triple: [Jayabaya, capital, Daha]
  • A. Daha chosen
    Daha was a prominent historical city in East Java that served as the political and cultural center of the medieval Kediri Kingdom in Indonesia.
  • B. Dalia
    Dalia is a central love interest and salon owner in the comedy film "You Don’t Mess with the Zohan," portrayed as a strong, independent Palestinian woman who becomes romantically involved with the title character.
  • C. Dinazad
    Dinazad is an alternate spelling of Dinarzad, the younger sister of Scheherazade in the classic Middle Eastern collection of tales known as One Thousand and One Nights.
  • D. Daza
    The Daza are an ethnic group of the central Sahara, primarily in Chad, known for their nomadic pastoralist lifestyle and close cultural and linguistic ties to the Toubou (Tebu) peoples.
  • E. Dawadmi
    Dawadmi is a town in central Saudi Arabia known as an important administrative and commercial center within Riyadh Province.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af026130bc8190ae3b0e9bec5ccad6 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576d5379081908300afbb3a6fe5e4 completed March 14, 2026, 2:55 p.m.
Created at: March 9, 2026, 3:43 p.m.