Triple

T6505103
Position Surface form Disambiguated ID Type / Status
Subject Southeast Sulawesi E149987 entity
Predicate hasCity P316 FINISHED
Object Andoolo
Andoolo is a small town that serves as an administrative center in the Indonesian province of Southeast Sulawesi.
 E600650 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: Andoolo | Statement: [Southeast Sulawesi, hasCity, Andoolo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Andoolo
Context triple: [Southeast Sulawesi, hasCity, Andoolo]
  • A. Erandol
    Erandol is a town in the Jalgaon district of Maharashtra, India, known for its agricultural economy and regional trading activities.
  • B. Yasa'ur
    Yasa'ur was a Mongol prince and military leader who played a significant role in the politics and conflicts of the Chagatai Khanate during the early 14th century.
  • C. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • D. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • E. Dorla
    Dorla are an indigenous Adivasi community of the Bastar region in central India, known for their distinct cultural traditions, language, and close relationship with forest-based livelihoods.
  • 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: Andoolo
Triple: [Southeast Sulawesi, hasCity, Andoolo]
Generated description
Andoolo is a small town that serves as an administrative center in the Indonesian province of Southeast Sulawesi.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Andoolo
Target entity description: Andoolo is a small town that serves as an administrative center in the Indonesian province of Southeast Sulawesi.
  • A. Erandol
    Erandol is a town in the Jalgaon district of Maharashtra, India, known for its agricultural economy and regional trading activities.
  • B. Yasa'ur
    Yasa'ur was a Mongol prince and military leader who played a significant role in the politics and conflicts of the Chagatai Khanate during the early 14th century.
  • C. Tynaarlo
    Tynaarlo is a municipality in the northeastern Netherlands known for its rural character and location between the cities of Groningen and Assen.
  • D. Dainzú
    Dainzú is an ancient Zapotec archaeological site in Oaxaca, Mexico, notable for its terraced architecture and carved stone reliefs depicting ballgame scenes.
  • E. Dorla
    Dorla are an indigenous Adivasi community of the Bastar region in central India, known for their distinct cultural traditions, language, and close relationship with forest-based livelihoods.
  • 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.