Triple

T15094016
Position Surface form Disambiguated ID Type / Status
Subject Aburrá Metropolitan Area E360491 entity
Predicate includesMunicipality P14658 FINISHED
Object Itagüí E179160 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: Itagüí | Statement: [Aburrá Metropolitan Area, includesMunicipality, Itagüí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Itagüí
Context triple: [Aburrá Metropolitan Area, includesMunicipality, Itagüí]
  • A. Itagüí chosen
    Itagüí is a densely populated industrial and commercial city in northwestern Colombia, located in the metropolitan area of Medellín.
  • B. Kurume
    Kurume is a mid-sized city in southwestern Japan known for its traditional textile industry, ramen culture, and location along the Chikugo River in Fukuoka Prefecture.
  • C. Minoh
    Minoh is a suburban city in northern Osaka Prefecture, Japan, known for its scenic Minoh Waterfall, autumn foliage, and residential communities.
  • D. Toda City
    Toda City is a municipality in Saitama Prefecture, Japan, located just north of Tokyo and known as a residential and commuter town within the Greater Tokyo metropolitan area.
  • E. Akishima
    Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054571a48190a57055c0d6e90f82 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae1f406081909d4925474370da86 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:04 a.m.