Triple

T35403660
Position Surface form Disambiguated ID Type / Status
Subject Lone district of Northern Samar E1023304 entity
Predicate contains P35 FINISHED
Object San Isidro, Northern Samar
San Isidro, Northern Samar is a coastal municipality in the Philippine province of Northern Samar known for its rural communities and fishing-based local economy.
 E2152409 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: San Isidro, Northern Samar | Statement: [Lone district of Northern Samar, contains, San Isidro, Northern Samar]
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: San Isidro, Northern Samar
Triple: [Lone district of Northern Samar, contains, San Isidro, Northern Samar]
Generated description
San Isidro, Northern Samar is a coastal municipality in the Philippine province of Northern Samar known for its rural communities and fishing-based local economy.

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_69f76df43ca4819098711ca4370f1bb9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7953fa72c8190bd737ef5dfa0ffc0 completed May 3, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a387cf6a1ec8190be8c46edb098845c completed June 22, 2026, 12:08 a.m.
NEDg Description generation batch_6a387d8bebac8190945e3bd73b0e9222 completed June 22, 2026, 12:10 a.m.
NED2 Entity disambiguation (via description) batch_6a387dfd11588190b56499799b37f578 completed June 22, 2026, 12:12 a.m.
Created at: May 3, 2026, 4:03 p.m.