Triple

T13417472
Position Surface form Disambiguated ID Type / Status
Subject Tana Toraja Regency E313249 entity
Predicate capital P234 FINISHED
Object Makale
Makale is a town in South Sulawesi, Indonesia, known as an administrative and cultural center of the Tana Toraja highlands.
E1038273 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: Makale | Statement: [Tana Toraja Regency, capital, Makale]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makale
Context triple: [Tana Toraja Regency, capital, Makale]
  • A. Nerekhta
    Nerekhta is a historic Russian town known for its well-preserved traditional architecture and cultural heritage within Kostroma Oblast.
  • B. The Paper
    The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
  • C. Warta
    Warta is a major river in western-central Poland that flows through several important cities before joining the Oder River.
  • D. Aamulehti
    Aamulehti is a prominent Finnish regional newspaper based in Tampere, known for its comprehensive coverage of local and national news.
  • E. Makatib
    Makatib is a collection of letters by the Persian Sufi poet Rumi, offering spiritual guidance, personal counsel, and insights into his mystical thought and relationships.
  • 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: Makale
Triple: [Tana Toraja Regency, capital, Makale]
Generated description
Makale is a town in South Sulawesi, Indonesia, known as an administrative and cultural center of the Tana Toraja highlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Makale
Target entity description: Makale is a town in South Sulawesi, Indonesia, known as an administrative and cultural center of the Tana Toraja highlands.
  • A. Nerekhta
    Nerekhta is a historic Russian town known for its well-preserved traditional architecture and cultural heritage within Kostroma Oblast.
  • B. The Paper
    The Paper is a 1994 American comedy-drama film directed by Ron Howard that follows the hectic, deadline-driven day at a New York City tabloid newspaper.
  • C. Warta
    Warta is a major river in western-central Poland that flows through several important cities before joining the Oder River.
  • D. Aamulehti
    Aamulehti is a prominent Finnish regional newspaper based in Tampere, known for its comprehensive coverage of local and national news.
  • E. Makatib
    Makatib is a collection of letters by the Persian Sufi poet Rumi, offering spiritual guidance, personal counsel, and insights into his mystical thought and relationships.
  • 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_69d806ad0c44819088833ae1ec9e9690 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb8416c8190a00dde0917c26f51 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f73082a2548190aefc0f202b84165c completed May 3, 2026, 11:24 a.m.
NEDg Description generation batch_69f7311f14988190989e319741ef0ccf completed May 3, 2026, 11:27 a.m.
NED2 Entity disambiguation (via description) batch_69f731e24d508190a896875210be3189 completed May 3, 2026, 11:30 a.m.
Created at: April 9, 2026, 9:39 p.m.