Triple

T9815663
Position Surface form Disambiguated ID Type / Status
Subject Halmahera E238395 entity
Predicate hasCity P316 FINISHED
Object Weda
Weda is a coastal town and administrative center on the island of Halmahera in Indonesia’s North Maluku province.
 E823371 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: Weda | Statement: [Halmahera, hasCity, Weda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Weda
Context triple: [Halmahera, hasCity, Weda]
  • A. Weda
    Weda is an alternative name for the Sawai language, an Austronesian language spoken in parts of eastern Indonesia.
  • B. Wakema
    Wakema is a town in Myanmar’s Ayeyarwady Region, known as the birthplace of former Burmese Prime Minister U Nu.
  • C. Valaquenta
    Valaquenta is a section of J.R.R. Tolkien’s legendarium that provides a mythological account of the Valar, the Maiar, and the cosmology of Middle-earth.
  • D. Teurnia
    Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
  • E. Wihro
    Wihro is the official mascot character created for the 2022 Mediterranean Games.
  • 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: Weda
Triple: [Halmahera, hasCity, Weda]
Generated description
Weda is a coastal town and administrative center on the island of Halmahera in Indonesia’s North Maluku province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Weda
Target entity description: Weda is a coastal town and administrative center on the island of Halmahera in Indonesia’s North Maluku province.
  • A. Weda
    Weda is an alternative name for the Sawai language, an Austronesian language spoken in parts of eastern Indonesia.
  • B. Wakema
    Wakema is a town in Myanmar’s Ayeyarwady Region, known as the birthplace of former Burmese Prime Minister U Nu.
  • C. Valaquenta
    Valaquenta is a section of J.R.R. Tolkien’s legendarium that provides a mythological account of the Valar, the Maiar, and the cosmology of Middle-earth.
  • D. Teurnia
    Teurnia was an important ancient Roman city that served as a major administrative and cultural center in the province of Noricum, located in what is now southern Austria.
  • E. Wihro
    Wihro is the official mascot character created for the 2022 Mediterranean Games.
  • 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_69ca84dfde1481909f47c286d715f892 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb2f341648190bf8343e1124085cb completed April 2, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc6c64dc8190979be34255dc22e5 completed April 5, 2026, 2:43 a.m.
NEDg Description generation batch_69d1cf7ce46c8190a7383086eb667b51 completed April 5, 2026, 2:57 a.m.
NED2 Entity disambiguation (via description) batch_69d1d0034dc081908182e3f873a2c584 completed April 5, 2026, 2:59 a.m.
Created at: March 30, 2026, 8:30 p.m.