Triple

T6505106
Position Surface form Disambiguated ID Type / Status
Subject Southeast Sulawesi E149987 entity
Predicate hasCity P316 FINISHED
Object Wanggudu
Wanggudu is a town in Indonesia’s Southeast Sulawesi province, known as a local administrative and population center in the region.
 E600653 NE FINISHED

How this triple was built (4 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: Wanggudu | Statement: [Southeast Sulawesi, hasCity, Wanggudu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Wanggudu
Context triple: [Southeast Sulawesi, hasCity, Wanggudu]
  • A. Watugaluh
    Watugaluh was an important historical city in Java that served as the political and administrative center of the Medang Kingdom.
  • B. Guting
    Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
  • C. Tawu
    Tawu is the indigenous name used by the Tao people, an Austronesian ethnic group native to Orchid Island in Taiwan.
  • D. Wanroij
    Wanroij is a village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Land van Cuijk.
  • E. Cindau
    Cindau is an alternative name for the Ndau language, a Bantu language spoken primarily in Mozambique and Zimbabwe.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wanggudu
Triple: [Southeast Sulawesi, hasCity, Wanggudu]
Generated description
Wanggudu is a town in Indonesia’s Southeast Sulawesi province, known as a local administrative and population center in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Wanggudu
Target entity description: Wanggudu is a town in Indonesia’s Southeast Sulawesi province, known as a local administrative and population center in the region.
  • A. Watugaluh
    Watugaluh was an important historical city in Java that served as the political and administrative center of the Medang Kingdom.
  • B. Guting
    Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
  • C. Tawu
    Tawu is the indigenous name used by the Tao people, an Austronesian ethnic group native to Orchid Island in Taiwan.
  • D. Wanroij
    Wanroij is a village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Land van Cuijk.
  • E. Cindau
    Cindau is an alternative name for the Ndau language, a Bantu language spoken primarily in Mozambique and Zimbabwe.
  • F. None of above. chosen

Provenance (5 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c69966ff708190902c88cb6b48e5d7 completed March 27, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb43db608190b785e77f6850bb6f completed March 27, 2026, 6:24 p.m.
NEDg Description generation batch_69c6cc96edd08190b0c0f1b49dd64160 completed March 27, 2026, 6:29 p.m.
NED2 Entity disambiguation (via description) batch_69c6cd8d15ec8190be5a8c5e3f201139 completed March 27, 2026, 6:33 p.m.
Created at: March 27, 2026, 1:43 p.m.