Triple

T9698800
Position Surface form Disambiguated ID Type / Status
Subject Alor–Pantar languages E234719 entity
Predicate includeLanguage P2177 FINISHED
Object Hamap
Hamap is a Papuan language spoken on the Alor–Pantar archipelago in eastern Indonesia.
 E815006 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: Hamap | Statement: [Alor–Pantar languages, includeLanguage, Hamap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hamap
Context triple: [Alor–Pantar languages, includeLanguage, Hamap]
  • A. Hama Tuma
    Hama Tuma is an Ethiopian writer and political satirist known for his sharp, critical short stories and essays that challenge authoritarianism and social injustice.
  • B. Hannut
    Hannut is a municipality in the French-speaking Walloon Region of Belgium, known for its rural character and location between Liège and Brussels.
  • C. Hamutal
    Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
  • D. Hachuamish
    Hachuamish is a traditional clan or band within the Duwamish people, an Indigenous Coast Salish group native to the Seattle area of Washington State.
  • E. Tepiman
    Tepiman is a subgroup of Uto-Aztecan languages spoken primarily in the southwestern United States and northern Mexico, including languages such as O'odham and Tepehuán.
  • 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: Hamap
Triple: [Alor–Pantar languages, includeLanguage, Hamap]
Generated description
Hamap is a Papuan language spoken on the Alor–Pantar archipelago in eastern Indonesia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hamap
Target entity description: Hamap is a Papuan language spoken on the Alor–Pantar archipelago in eastern Indonesia.
  • A. Hama Tuma
    Hama Tuma is an Ethiopian writer and political satirist known for his sharp, critical short stories and essays that challenge authoritarianism and social injustice.
  • B. Hannut
    Hannut is a municipality in the French-speaking Walloon Region of Belgium, known for its rural character and location between Liège and Brussels.
  • C. Hamutal
    Hamutal was a queen of Judah, known as the mother of the last king of Judah, Zedekiah, during the final years before the Babylonian exile.
  • D. Hachuamish
    Hachuamish is a traditional clan or band within the Duwamish people, an Indigenous Coast Salish group native to the Seattle area of Washington State.
  • E. Tepiman
    Tepiman is a subgroup of Uto-Aztecan languages spoken primarily in the southwestern United States and northern Mexico, including languages such as O'odham and Tepehuán.
  • 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d3d425c8190b652d84186b5ce9f completed April 1, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1912a551c8190bd6b48790f117f71 completed April 4, 2026, 10:31 p.m.
NEDg Description generation batch_69d193d8dd7c819094ca47105c3135e6 completed April 4, 2026, 10:42 p.m.
NED2 Entity disambiguation (via description) batch_69d1943d67988190aac089266d2d4abc completed April 4, 2026, 10:44 p.m.
Created at: March 30, 2026, 8:18 p.m.