Triple

T1486445
Position Surface form Disambiguated ID Type / Status
Subject Flores E29474 entity
Predicate hasCity P316 FINISHED
Object Bajawa
Bajawa is a small highland town in central Flores, Indonesia, known for its cool climate, traditional Ngada culture, and nearby volcanic and megalithic sites.
E182175 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: Bajawa | Statement: [Flores, hasCity, Bajawa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bajawa
Context triple: [Flores, hasCity, Bajawa]
  • A. Labuan Bajo
    Labuan Bajo is a coastal town on the Indonesian island of Flores that serves as the main gateway for tourists visiting Komodo National Park and its famous Komodo dragons.
  • B. Bukittinggi
    Bukittinggi is a historic highland city in West Sumatra, Indonesia, renowned as a major hub of Minangkabau culture, history, and tourism.
  • C. Mataram
    Mataram was the principal urban and political center of the early Javanese Medang Kingdom, serving as a key hub of power and culture in central Java.
  • D. Mataram
    Mataram is the capital and largest city of the Indonesian province of West Nusa Tenggara, located on the island of Lombok.
  • 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: Bajawa
Triple: [Flores, hasCity, Bajawa]
Generated description
Bajawa is a small highland town in central Flores, Indonesia, known for its cool climate, traditional Ngada culture, and nearby volcanic and megalithic sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bajawa
Target entity description: Bajawa is a small highland town in central Flores, Indonesia, known for its cool climate, traditional Ngada culture, and nearby volcanic and megalithic sites.
  • A. Labuan Bajo
    Labuan Bajo is a coastal town on the Indonesian island of Flores that serves as the main gateway for tourists visiting Komodo National Park and its famous Komodo dragons.
  • B. Bukittinggi
    Bukittinggi is a historic highland city in West Sumatra, Indonesia, renowned as a major hub of Minangkabau culture, history, and tourism.
  • C. Mataram
    Mataram was the principal urban and political center of the early Javanese Medang Kingdom, serving as a key hub of power and culture in central Java.
  • D. Mataram
    Mataram is the capital and largest city of the Indonesian province of West Nusa Tenggara, located on the island of Lombok.
  • 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_69a498da82e08190ba833330d05f380f completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6a3325881909bbc55efc04ad60f completed March 1, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad51a514908190b782eb1ca98d5b4c completed March 8, 2026, 10:38 a.m.
NEDg Description generation batch_69ad525e5c908190bad4fc58342c3ef2 completed March 8, 2026, 10:41 a.m.
NED2 Entity disambiguation (via description) batch_69ad52bfdbec81908f7240c46ce11888 completed March 8, 2026, 10:43 a.m.
Created at: March 1, 2026, 8:12 p.m.