Triple

T3080496
Position Surface form Disambiguated ID Type / Status
Subject Old Town (Kota Lama) E64244 entity
Predicate hasLocalName P6353 FINISHED
Object Kota Lama E64244 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: Kota Lama | Statement: [Old Town (Kota Lama), hasLocalName, Kota Lama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kota Lama
Context triple: [Old Town (Kota Lama), hasLocalName, Kota Lama]
  • A. Ciudad Vieja
    Ciudad Vieja is the historic old town of Montevideo, Uruguay, known for its colonial architecture, cultural landmarks, and vibrant portside atmosphere.
  • B. Old Town (Kota Lama) chosen
    Old Town (Kota Lama) is a historic district in Semarang, Indonesia, renowned for its well-preserved Dutch colonial architecture and heritage landmarks.
  • C. Barrio Antiguo
    Barrio Antiguo is a historic neighborhood in Monterrey, Mexico, known for its preserved colonial architecture, cultural venues, nightlife, and vibrant arts scene.
  • D. Florencia
    Florencia is a street in Mexico City that intersects at the Glorieta del Ángel, a major roundabout surrounding the iconic Angel of Independence monument.
  • E. San Borja
    San Borja is a primarily residential and commercial district in Lima, Peru, known for its middle- to upper-class neighborhoods, green areas, and cultural institutions.
  • 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_69ad857bb4c88190a4cf27893fcabed8 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada1a9d61081909953eb2f4ad4537e completed March 8, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1f89443a4819091dafc560b45cc26 completed March 11, 2026, 11:19 p.m.
Created at: March 8, 2026, 3:03 p.m.