Triple

T16944040
Position Surface form Disambiguated ID Type / Status
Subject Dagupan E411021 entity
Predicate hasBodyOfWater P1778 FINISHED
Object Tanap River
The Tanap River is a waterway associated with the city of Dagupan in the Philippines, contributing to its local river system and waterways.
E1930187 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: Tanap River | Statement: [Dagupan, hasBodyOfWater, Tanap River]
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: Tanap River
Triple: [Dagupan, hasBodyOfWater, Tanap River]
Generated description
The Tanap River is a waterway associated with the city of Dagupan in the Philippines, contributing to its local river system and waterways.

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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cfb08da88190b07c32652bbc1534 completed April 18, 2026, 6:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b06199e48190a1da91f03a6f8712 completed June 10, 2026, 12:31 a.m.
NEDg Description generation batch_6a28b1b3d41481908b42370b7ad16ba4 completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2561d808190b5fbfc96e46634df completed June 10, 2026, 12:39 a.m.
Created at: April 10, 2026, 5:31 a.m.