Triple

T6472906
Position Surface form Disambiguated ID Type / Status
Subject Kalanguya language E145997 entity
Predicate hasAlternativeName P39 FINISHED
Object Kalangoya
Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
 E596593 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: Kalangoya | Statement: [Kalanguya language, hasAlternativeName, Kalangoya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kalangoya
Context triple: [Kalanguya language, hasAlternativeName, Kalangoya]
  • A. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • B. Massinga
    Massinga is a coastal town in southern Mozambique that serves as an important local center within Inhambane Province.
  • C. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • D. Kanyaga
    "Kanyaga" is a popular Tanzanian Bongo Flava hit song by Diamond Platnumz known for its energetic beat and danceable style.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • 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: Kalangoya
Triple: [Kalanguya language, hasAlternativeName, Kalangoya]
Generated description
Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kalangoya
Target entity description: Kalangoya is an alternative name for the Kalanguya language, an Austronesian language spoken by indigenous communities in the northern Philippines.
  • A. Kalangala
    Kalangala is a town on Uganda’s Ssese Islands in Lake Victoria, serving as the administrative and commercial center of Kalangala District.
  • B. Massinga
    Massinga is a coastal town in southern Mozambique that serves as an important local center within Inhambane Province.
  • C. Monguno
    Monguno is a town and local government area in Borno State, northeastern Nigeria, known for its strategic location and role in regional security dynamics.
  • D. Kanyaga
    "Kanyaga" is a popular Tanzanian Bongo Flava hit song by Diamond Platnumz known for its energetic beat and danceable style.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a3188488190a1b7452ede91ba5e completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6539fe1e08190ae0004ed2113e319 completed March 27, 2026, 9:53 a.m.
NEDg Description generation batch_69c6564a79b08190818ecd149aa34698 completed March 27, 2026, 10:04 a.m.
NED2 Entity disambiguation (via description) batch_69c6570477348190bdc1f0b2eb781c84 completed March 27, 2026, 10:08 a.m.
Created at: March 22, 2026, 4:50 p.m.