Triple

T20454676
Position Surface form Disambiguated ID Type / Status
Subject Jaflong E501744 entity
Predicate locatedOnRiver P165 FINISHED
Object Piyain River
Piyain River is a scenic transboundary river flowing through northeastern Bangladesh and northeastern India, known for its clear waters, stone beds, and popular tourist spots like Jaflong.
E2261061 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: Piyain River | Statement: [Jaflong, locatedOnRiver, Piyain 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: Piyain River
Triple: [Jaflong, locatedOnRiver, Piyain River]
Generated description
Piyain River is a scenic transboundary river flowing through northeastern Bangladesh and northeastern India, known for its clear waters, stone beds, and popular tourist spots like Jaflong.

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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e68d04ca4081909b428c31d16fca10 completed April 20, 2026, 8:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a418521eb0c81908464452a197e4967 completed June 28, 2026, 8:33 p.m.
NEDg Description generation batch_6a418614ac648190bdad4426fee791fb completed June 28, 2026, 8:37 p.m.
NED2 Entity disambiguation (via description) batch_6a4186d235348190a89738f739b88fdb completed June 28, 2026, 8:40 p.m.
Created at: April 16, 2026, 11:32 a.m.