Triple

T37851198
Position Surface form Disambiguated ID Type / Status
Subject 4th District of Iloilo E944059 entity
Predicate contains P35 FINISHED
Object Municipality of Banate, Iloilo
The Municipality of Banate is a coastal town in the province of Iloilo in the Philippines, known for its fishing industry and scenic views of Banate Bay.
E2250512 NE FINISHED

How this triple was built (2 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: Municipality of Banate, Iloilo | Statement: [4th District of Iloilo, contains, Municipality of Banate, Iloilo]
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: Municipality of Banate, Iloilo
Triple: [4th District of Iloilo, contains, Municipality of Banate, Iloilo]
Generated description
The Municipality of Banate is a coastal town in the province of Iloilo in the Philippines, known for its fishing industry and scenic views of Banate Bay.

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_69f76eed4d9c81908b1b71ba9e3b61fe completed May 3, 2026, 3:51 p.m.
NER Named-entity recognition batch_69fbb2255c488190a0cfc072fa2a4e71 completed May 6, 2026, 9:27 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4117e3515c8190bcb0af9be4cae677 completed June 28, 2026, 12:47 p.m.
NEDg Description generation batch_6a4124f9b46c81909a8ca502ad360e05 completed June 28, 2026, 1:43 p.m.
NED2 Entity disambiguation (via description) batch_6a4125577f3c81908465945fc5dbb1ca completed June 28, 2026, 1:44 p.m.
Created at: May 3, 2026, 4:19 p.m.