Triple

T15722708
Position Surface form Disambiguated ID Type / Status
Subject Sagay E381139 entity
Predicate hasBarangay P29835 FINISHED
Object Molocaboc
Molocaboc is a coastal barangay of Sagay City in Negros Occidental, Philippines, known for its fishing communities and surrounding marine resources.
 E1173266 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: Molocaboc | Statement: [Sagay, hasBarangay, Molocaboc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Molocaboc
Context triple: [Sagay, hasBarangay, Molocaboc]
  • A. Molibagu
    Molibagu is a town in North Sulawesi, Indonesia, serving as the administrative and economic center of South Bolaang Mongondow Regency.
  • B. Moclus
    Moclus is the industrial, militaristic, and rigidly structured home planet of the all-male Moclan species in the science fiction series "The Orville."
  • C. Motal
    Motal is a small town in present-day Belarus, historically part of the Russian Empire, known as the birthplace of Israel’s first president, Chaim Weizmann.
  • D. Mabor
    Mabor is a tire brand owned by Continental AG, known for producing affordable passenger and commercial vehicle tires.
  • E. Liboc
    Liboc is a residential district in the western part of Prague known for its green spaces and proximity to the Divoká Šárka nature reserve.
  • 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: Molocaboc
Triple: [Sagay, hasBarangay, Molocaboc]
Generated description
Molocaboc is a coastal barangay of Sagay City in Negros Occidental, Philippines, known for its fishing communities and surrounding marine resources.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Molocaboc
Target entity description: Molocaboc is a coastal barangay of Sagay City in Negros Occidental, Philippines, known for its fishing communities and surrounding marine resources.
  • A. Molibagu
    Molibagu is a town in North Sulawesi, Indonesia, serving as the administrative and economic center of South Bolaang Mongondow Regency.
  • B. Moclus
    Moclus is the industrial, militaristic, and rigidly structured home planet of the all-male Moclan species in the science fiction series "The Orville."
  • C. Motal
    Motal is a small town in present-day Belarus, historically part of the Russian Empire, known as the birthplace of Israel’s first president, Chaim Weizmann.
  • D. Mabor
    Mabor is a tire brand owned by Continental AG, known for producing affordable passenger and commercial vehicle tires.
  • E. Liboc
    Liboc is a residential district in the western part of Prague known for its green spaces and proximity to the Divoká Šárka nature reserve.
  • 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fb1fdd4819088f3e243263e5f73 completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff82f68bf881909e5ad8a6ab81684a completed May 9, 2026, 6:54 p.m.
NEDg Description generation batch_69ff8388b3588190ae55c123bb19cb2c completed May 9, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69ff84125e808190a4d465d9effad639 completed May 9, 2026, 6:59 p.m.
Created at: April 10, 2026, 4:45 a.m.