Triple

T1148134
Position Surface form Disambiguated ID Type / Status
Subject Makassar E23614 entity
Predicate historicalName P65 FINISHED
Object Ujung Pandang E23614 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: Ujung Pandang | Statement: [Makassar, historicalName, Ujung Pandang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ujung Pandang
Context triple: [Makassar, historicalName, Ujung Pandang]
  • A. 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.
  • B. Bandung metropolitan area
    The Bandung metropolitan area is a major urban and economic region in West Java, Indonesia, centered on the city of Bandung and its surrounding suburbs and satellite towns.
  • C. 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.
  • D. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • E. Makassar chosen
    Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
  • 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_69a493f0d32c8190ac74bad3c87f2641 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc7041248190893e4c655dbd0604 completed March 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69acbf13304881908aa74d92ef7b1c86 completed March 8, 2026, 12:13 a.m.
Created at: March 1, 2026, 7:44 p.m.