Triple

T17419396
Position Surface form Disambiguated ID Type / Status
Subject Pasaman Regency E423571 entity
Predicate capital P234 FINISHED
Object Lubuk Sikaping
Lubuk Sikaping is a town in West Sumatra, Indonesia, that serves as the administrative and economic center of Pasaman Regency.
E1268147 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: Lubuk Sikaping | Statement: [Pasaman Regency, capital, Lubuk Sikaping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lubuk Sikaping
Context triple: [Pasaman Regency, capital, Lubuk Sikaping]
  • A. Lubuk Alung
    Lubuk Alung is a town in West Sumatra, Indonesia, known as an important local administrative and transportation hub within Padang Pariaman Regency.
  • B. Lubuk Basung
    Lubuk Basung is the administrative and economic center of Agam Regency in West Sumatra, Indonesia.
  • C. Gosong Rengat
    Gosong Rengat is a small island area within Indonesia’s Thousand Islands Regency, known as part of the scattered archipelago off the coast of Jakarta.
  • D. Muaro Sijunjung
    Muaro Sijunjung is the main administrative and urban center of Sijunjung Regency in West Sumatra, Indonesia.
  • E. Kampar
    Kampar is a town and district in Perak, Malaysia, historically notable as the site of a major World War II battle between British Commonwealth and Japanese forces.
  • 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: Lubuk Sikaping
Triple: [Pasaman Regency, capital, Lubuk Sikaping]
Generated description
Lubuk Sikaping is a town in West Sumatra, Indonesia, that serves as the administrative and economic center of Pasaman Regency.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lubuk Sikaping
Target entity description: Lubuk Sikaping is a town in West Sumatra, Indonesia, that serves as the administrative and economic center of Pasaman Regency.
  • A. Lubuk Alung
    Lubuk Alung is a town in West Sumatra, Indonesia, known as an important local administrative and transportation hub within Padang Pariaman Regency.
  • B. Lubuk Basung
    Lubuk Basung is the administrative and economic center of Agam Regency in West Sumatra, Indonesia.
  • C. Gosong Rengat
    Gosong Rengat is a small island area within Indonesia’s Thousand Islands Regency, known as part of the scattered archipelago off the coast of Jakarta.
  • D. Muaro Sijunjung
    Muaro Sijunjung is the main administrative and urban center of Sijunjung Regency in West Sumatra, Indonesia.
  • E. Kampar
    Kampar is a town and district in Perak, Malaysia, historically notable as the site of a major World War II battle between British Commonwealth and Japanese forces.
  • 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_69d889d7d27c819088486ce3f0627fa1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44236419c8190a106748bca6f30cd completed April 19, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01a8041f548190a076b10516ccfced completed May 11, 2026, 9:57 a.m.
NEDg Description generation batch_6a01a8d7e05c8190aceb0795a430fee7 completed May 11, 2026, 10 a.m.
NED2 Entity disambiguation (via description) batch_6a01a943fdec8190a875c7eb56c742da completed May 11, 2026, 10:02 a.m.
Created at: April 10, 2026, 5:46 a.m.