Triple

T1125954
Position Surface form Disambiguated ID Type / Status
Subject Tangkuban Perahu E24719 entity
Predicate nearbyCity P350 FINISHED
Object Lembang E121874 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: Lembang | Statement: [Tangkuban Perahu, nearbyCity, Lembang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lembang
Context triple: [Tangkuban Perahu, nearbyCity, Lembang]
  • A. Lembang highlands chosen
    Lembang Highlands is a cool, scenic upland area near Bandung in West Java, Indonesia, known for its tea plantations, volcanic landscapes, and popular nature-based tourist attractions.
  • B. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • C. Garut
    Garut is a regency and town in West Java, Indonesia, known for its Sundanese culture, cool highland climate, and agricultural products such as vegetables and sheep.
  • D. Bogor
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • E. Bandung
    Bandung is a large Indonesian city on the island of Java known for its cool climate, universities, colonial and art deco architecture, and role as a center of culture and technology.
  • 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_69a4940712c88190aa244f3fc6070a65 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bbdc2718819094f5519ffb56993b completed March 1, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac5eab1e6481908c175e175ae4743a completed March 7, 2026, 5:21 p.m.
Created at: March 1, 2026, 7:44 p.m.