Triple

T16337404
Position Surface form Disambiguated ID Type / Status
Subject Southern Cuba E396711 entity
Predicate containsCity P294 FINISHED
Object Manzanillo E531127 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: Manzanillo | Statement: [Southern Cuba, containsCity, Manzanillo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manzanillo
Context triple: [Southern Cuba, containsCity, Manzanillo]
  • A. Manzanillo
    Manzanillo is a major Pacific coastal city in western Mexico known for its busy commercial port and popular beach tourism.
  • B. Manzanillo chosen
    Manzanillo is a coastal city in southeastern Cuba known as an important port and commercial center on the Gulf of Guacanayabo.
  • C. Minatitlán
    Minatitlán is a small inland municipality in the Mexican state of Colima, known for its rural character and agricultural activities.
  • D. Minatitlán
    Minatitlán is an industrial city in the Mexican state of Veracruz, known for its major oil refinery and strategic location in the petroleum industry.
  • E. Puerto Juárez
    Puerto Juárez is a coastal locality and ferry port near Cancún in Quintana Roo, Mexico, serving as a gateway to nearby islands such as Isla Mujeres.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4e524448190870a6ef569017b56 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0026193a3c81909c640426ab798c1c completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 5:07 a.m.