Triple

T11572952
Position Surface form Disambiguated ID Type / Status
Subject Oton E274434 entity
Predicate hasBarangay P29835 FINISHED
Object Turu-yan
Turu-yan is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
 E935411 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: Turu-yan | Statement: [Oton, hasBarangay, Turu-yan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Turu-yan
Context triple: [Oton, hasBarangay, Turu-yan]
  • A. Kamayurá
    Kamayurá is an indigenous people of Brazil’s Upper Xingu region, known for their distinct Tupi–Guaraní language and rich ceremonial and ritual traditions.
  • B. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • C. Toramana
    Toramana was a prominent Huna ruler in early 6th-century northern India, known for his extensive military campaigns and significant role in weakening the Gupta Empire.
  • D. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • E. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • 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: Turu-yan
Triple: [Oton, hasBarangay, Turu-yan]
Generated description
Turu-yan is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Turu-yan
Target entity description: Turu-yan is a barangay (village-level administrative division) within the municipality of Oton in the province of Iloilo, Philippines.
  • A. Kamayurá
    Kamayurá is an indigenous people of Brazil’s Upper Xingu region, known for their distinct Tupi–Guaraní language and rich ceremonial and ritual traditions.
  • B. Takamikura
    Takamikura is the ornate imperial throne used in Kyoto for the enthronement ceremonies of Japanese emperors.
  • C. Toramana
    Toramana was a prominent Huna ruler in early 6th-century northern India, known for his extensive military campaigns and significant role in weakening the Gupta Empire.
  • D. Nuriro
    Nuriro is a class of South Korean intercity passenger trains operated by Korail, providing medium-speed rail services on various routes.
  • E. Seishirō
    Seishirō is a Japanese given name commonly used for male individuals.
  • 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_69d6aae5ac3c81908d2b0a3a665665b2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d88dd6913881908becf188c0a7a275 completed April 10, 2026, 5:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69e713d18ccc8190a63256c3cc1c2f59 completed April 21, 2026, 6:06 a.m.
NEDg Description generation batch_69e720f4015c81909ba7973c3e781985 completed April 21, 2026, 7:02 a.m.
NED2 Entity disambiguation (via description) batch_69e75a7a04c88190bb8f3dd3f3e435ef completed April 21, 2026, 11:07 a.m.
Created at: April 8, 2026, 9:38 p.m.