Triple

T434084
Position Surface form Disambiguated ID Type / Status
Subject Hiligaynon language E9774 entity
Predicate alternativeName P39 FINISHED
Object Ilonggo
Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
 E58819 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: Ilonggo | Statement: [Hiligaynon language, alternativeName, Ilonggo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ilonggo
Context triple: [Hiligaynon language, alternativeName, Ilonggo]
  • A. Batabanó
    Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
  • B. Kassaman
    Kassaman is the national anthem of Algeria, known for its revolutionary lyrics that honor the struggle for independence from French colonial rule.
  • C. Olosega
    Olosega is a small volcanic island in the Manuʻa group of American Samoa, known for its dramatic cliffs, lush vegetation, and connection by bridge to the neighboring island of Ofu.
  • D. Tontola
    Tontola is a small locality or hamlet that forms part of the municipality of Predappio in the Emilia-Romagna region of Italy.
  • E. Lapa
    Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • 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: Ilonggo
Triple: [Hiligaynon language, alternativeName, Ilonggo]
Generated description
Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ilonggo
Target entity description: Ilonggo is a major Austronesian language spoken primarily in Western Visayas and parts of Mindanao in the Philippines.
  • A. Batabanó
    Batabanó is a coastal municipality in western Cuba known for its fishing industry and ferry connections to nearby islands.
  • B. Kassaman
    Kassaman is the national anthem of Algeria, known for its revolutionary lyrics that honor the struggle for independence from French colonial rule.
  • C. Olosega
    Olosega is a small volcanic island in the Manuʻa group of American Samoa, known for its dramatic cliffs, lush vegetation, and connection by bridge to the neighboring island of Ofu.
  • D. Tontola
    Tontola is a small locality or hamlet that forms part of the municipality of Predappio in the Emilia-Romagna region of Italy.
  • E. Lapa
    Lapa is a historic and bohemian neighborhood in Rio de Janeiro, Brazil, famous for its vibrant nightlife, samba clubs, and iconic aqueduct arches.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ef0a008c8190ae0aa25e4df9c35f completed Feb. 28, 2026, 1:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69a457fba1d08190a8eb41271b59a693 completed March 1, 2026, 3:15 p.m.
NEDg Description generation batch_69a45d7d7bc881908b0862cfe82b73c1 completed March 1, 2026, 3:38 p.m.
NED2 Entity disambiguation (via description) batch_69a45dd685cc819095bc100ce6c23a78 completed March 1, 2026, 3:40 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.