Triple

T9008472
Position Surface form Disambiguated ID Type / Status
Subject Condado tourist district E215404 entity
Predicate partOf P40 FINISHED
Object Santurce E140044 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: Santurce | Statement: [Condado tourist district, partOf, Santurce]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santurce
Context triple: [Condado tourist district, partOf, Santurce]
  • A. Santurce chosen
    Santurce is a densely populated and culturally vibrant district of San Juan, Puerto Rico, known for its arts scene, nightlife, and historic neighborhoods.
  • B. Cataño
    Cataño is a small coastal municipality in northern Puerto Rico, known for its waterfront views of Old San Juan and its historic rum distillery.
  • C. Hato Corozal
    Hato Corozal is a rural municipality in eastern Colombia known for its cattle ranching and llanero (plains) culture within the Casanare Department.
  • D. Loíza
    Loíza is a coastal municipality in Puerto Rico known for its rich Afro-Puerto Rican culture, traditional Bomba music and dance, and vibrant religious and folk festivals.
  • E. Hatillo
    Hatillo is an urban district within the canton of San José in Costa Rica, known for its dense residential neighborhoods and proximity to the capital’s downtown area.
  • 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_69ca83a2bf088190986ee7a8eb90407d completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc69bed8588190afc9cbca12b75a3b completed April 1, 2026, 12:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0ec84348190944a2310a6a60448 completed April 3, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:06 p.m.