Triple

T2942863
Position Surface form Disambiguated ID Type / Status
Subject South Sulawesi E79427 entity
Predicate hasCity P316 FINISHED
Object Palopo
Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
 E318743 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: Palopo | Statement: [South Sulawesi, hasCity, Palopo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Palopo
Context triple: [South Sulawesi, hasCity, Palopo]
  • A. Kendari
    Kendari is the capital and largest city of Southeast Sulawesi Province on the Indonesian island of Sulawesi, known as a regional center for trade and maritime activities.
  • B. Parepare
    Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
  • C. Makassar
    Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
  • D. Palu
    Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
  • E. Payakumbuh
    Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
  • 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: Palopo
Triple: [South Sulawesi, hasCity, Palopo]
Generated description
Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Palopo
Target entity description: Palopo is a coastal city in Indonesia known as an important regional center in the province of South Sulawesi.
  • A. Kendari
    Kendari is the capital and largest city of Southeast Sulawesi Province on the Indonesian island of Sulawesi, known as a regional center for trade and maritime activities.
  • B. Parepare
    Parepare is a coastal city and important port on the western coast of South Sulawesi, Indonesia.
  • C. Makassar
    Makassar is a major port city on the southwest coast of Sulawesi known historically as a key maritime trading hub in eastern Indonesia.
  • D. Palu
    Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
  • E. Payakumbuh
    Payakumbuh is a city in West Sumatra, Indonesia, known as an important hub of Minangkabau culture, cuisine, and traditional arts.
  • 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_69ad8b1089588190b74d9e2505e45762 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9871fc908190ad90e5b01b476b3f completed March 8, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69b12e1d59a48190b06ebe298590feb8 completed March 11, 2026, 8:55 a.m.
NEDg Description generation batch_69b12f188c7c81908d1d575252dc4bda completed March 11, 2026, 9 a.m.
NED2 Entity disambiguation (via description) batch_69b1c9bccb3081909e6869b5cba68117 completed March 11, 2026, 7:59 p.m.
Created at: March 8, 2026, 2:56 p.m.