Triple

T441453
Position Surface form Disambiguated ID Type / Status
Subject Yoruba E10121 entity
Predicate historicalCenter P2536 FINISHED
Object Oyo E13198 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: Oyo | Statement: [Yoruba, historicalCenter, Oyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oyo
Context triple: [Yoruba, historicalCenter, Oyo]
  • A. Goa
    Goa is a coastal state on India’s western shore known for its beaches, distinctive blend of Indian and Portuguese heritage, and vibrant tourism industry.
  • B. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • C. Kerala
    Kerala is a coastal state in southwestern India known for its backwaters, high literacy rate, distinctive Malayalam culture, and strong traditions in art, Ayurveda, and religious diversity.
  • D. Kano chosen
    Kano is a major commercial and industrial city in northern Nigeria and one of the country’s oldest urban centers.
  • E. Gujarat
    Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
  • 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_69a2e8465ef481909655c681b01e2986 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2ef2af84881909635ebbbb3465b1b completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a43e71ec4c8190ac1b80c01e0e83ad completed March 1, 2026, 1:26 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.