Triple

T12238106
Position Surface form Disambiguated ID Type / Status
Subject Kai Islands E291653 entity
Predicate hasLargestTown P847 FINISHED
Object Tual
Tual is the main urban and administrative center of the Kai Islands in Indonesia’s Maluku province.
E970884 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: Tual | Statement: [Kai Islands, hasLargestTown, Tual]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tual
Context triple: [Kai Islands, hasLargestTown, Tual]
  • A. Tidore
    Tidore is an island and historic sultanate in eastern Indonesia that was once a major center of the regional spice trade.
  • B. Biak
    Biak is an Austronesian language spoken primarily on Biak Island and nearby areas in Papua, Indonesia.
  • C. Donggala
    Donggala is a coastal town and regency in Indonesia known historically as a key port and administrative center in Central Sulawesi.
  • D. Kolaka
    Kolaka is a coastal town and important regional center on the island of Sulawesi in Indonesia, known for its mining activities and role as a transport hub in Southeast Sulawesi.
  • E. Tobelo
    Tobelo is a coastal town and important regional center in northern Halmahera, North Maluku, Indonesia.
  • 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: Tual
Triple: [Kai Islands, hasLargestTown, Tual]
Generated description
Tual is the main urban and administrative center of the Kai Islands in Indonesia’s Maluku province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tual
Target entity description: Tual is the main urban and administrative center of the Kai Islands in Indonesia’s Maluku province.
  • A. Tidore
    Tidore is an island and historic sultanate in eastern Indonesia that was once a major center of the regional spice trade.
  • B. Biak
    Biak is an Austronesian language spoken primarily on Biak Island and nearby areas in Papua, Indonesia.
  • C. Donggala
    Donggala is a coastal town and regency in Indonesia known historically as a key port and administrative center in Central Sulawesi.
  • D. Kolaka
    Kolaka is a coastal town and important regional center on the island of Sulawesi in Indonesia, known for its mining activities and role as a transport hub in Southeast Sulawesi.
  • E. Tobelo
    Tobelo is a coastal town and important regional center in northern Halmahera, North Maluku, Indonesia.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cb45340819093365f8efdf85f75 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60ab3ae2481908f65d8ac61a6b2e4 completed May 2, 2026, 2:31 p.m.
NEDg Description generation batch_69f60bdd8d508190813178ff4c77afcf completed May 2, 2026, 2:36 p.m.
NED2 Entity disambiguation (via description) batch_69f60c67c680819087630d190d0a008f completed May 2, 2026, 2:38 p.m.
Created at: April 8, 2026, 9:51 p.m.