Triple

T10943988
Position Surface form Disambiguated ID Type / Status
Subject Columbia, Missouri E258546 entity
Predicate hasNickname P39 FINISHED
Object CoMo E586095 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: CoMo | Statement: [Columbia, Missouri, hasNickname, CoMo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CoMo
Context triple: [Columbia, Missouri, hasNickname, CoMo]
  • A. CoMo chosen
    CoMo is a common nickname for Columbia, Missouri, a mid-sized college town known for the University of Missouri and its vibrant arts and music scene.
  • B. Cembo
    Cembo is a residential and commercial barangay in Makati City, Philippines, known for its dense urban community and proximity to major business districts.
  • C. Komae
    Komae is a small residential city in Tokyo Metropolis, Japan, known for its suburban character and proximity to central Tokyo.
  • D. Kombe
    Kombe is a Bantu language spoken by the Kombe people of coastal Equatorial Guinea and nearby regions, closely related to other Ndowe-area languages.
  • E. Chomu
    Chomu is a historic town in the Indian state of Rajasthan, known for its traditional architecture and cultural heritage.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c4d59481908a5900fc8cf9ecc3 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c2dea008190af68336a096b7f7c completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.