Triple

T1807585
Position Surface form Disambiguated ID Type / Status
Subject Haya bint Hussein E40255 entity
Predicate givenName P17 FINISHED
Object Haya E42394 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: Haya | Statement: [Haya bint Hussein, givenName, Haya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haya
Context triple: [Haya bint Hussein, givenName, Haya]
  • A. Haya chosen
    Haya is a feminine given name of Arabic origin, commonly used in the Middle East and among Arabic-speaking communities.
  • B. Yahi
    The Yahi were a small Native American group from northern California, known for being among the last surviving independent Indigenous peoples in the region and for the story of Ishi, their last known member.
  • C. Hani
    The Hani are an ethnic minority group in China, primarily known for their terraced rice farming, distinctive traditional dress, and rich folk culture in the mountainous regions of Yunnan.
  • D. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • E. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • 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_69a88643a3388190a612f2ebe1fb29e7 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa6599f35c8190aefd20773365fdcf completed March 6, 2026, 5:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69adb5e137bc81908294dd6b67789526 completed March 8, 2026, 5:46 p.m.
Created at: March 4, 2026, 7:32 p.m.