Triple

T14532437
Position Surface form Disambiguated ID Type / Status
Subject Universidad de Colima E340947 entity
Predicate hasCampusIn P4623 FINISHED
Object Tecomán E1065133 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: Tecomán | Statement: [Universidad de Colima, hasCampusIn, Tecomán]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tecomán
Context triple: [Universidad de Colima, hasCampusIn, Tecomán]
  • A. Tecomán chosen
    Tecomán is a city in the Mexican state of Colima known for its agricultural production, particularly limes, and its proximity to Pacific coast beaches.
  • B. Guasave
    Guasave is a coastal agricultural and fishing city and municipality in the north-central region of the Mexican state of Sinaloa.
  • C. Tuxpan
    Tuxpan is a town and municipality in the Mexican state of Nayarit, known for its agricultural economy and traditional cultural festivals.
  • D. Tuxpan
    Tuxpan is a port city in the Mexican state of Veracruz, known for its Gulf Coast location and historical role as a departure point in the Cuban Revolution.
  • E. Tepatitlán de Morelos
    Tepatitlán de Morelos is a prominent city in Mexico known for its agricultural production, religious traditions, and vibrant regional culture.
  • 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dea053f9bc8190901b9d321811d881 completed April 14, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff2ce36ce08190930e791e2837d1a5 completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 1:22 a.m.