Triple

T26140394
Position Surface form Disambiguated ID Type / Status
Subject Pudukkottai district E659498 entity
Predicate hasRiver P165 FINISHED
Object Pamaniyar River
The Pamaniyar River is a regional watercourse in the Indian state of Tamil Nadu that flows through the Pudukkottai district and supports local agriculture and ecosystems.
E2291262 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: Pamaniyar River | Statement: [Pudukkottai district, hasRiver, Pamaniyar 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: Pamaniyar River
Triple: [Pudukkottai district, hasRiver, Pamaniyar River]
Generated description
The Pamaniyar River is a regional watercourse in the Indian state of Tamil Nadu that flows through the Pudukkottai district and supports local agriculture and ecosystems.

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_69ee5bc3c20c8190bf2cf272f4170e95 completed April 26, 2026, 6:38 p.m.
NER Named-entity recognition batch_69f60be435b48190a389ebb5a4537a16 completed May 2, 2026, 2:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5c42c6b3c481909e6f27497cfc3245 completed July 19, 2026, 3:21 a.m.
NEDg Description generation batch_6a5c4385b4fc819082e56f9f42c23c8d completed July 19, 2026, 3:24 a.m.
NED2 Entity disambiguation (via description) batch_6a5c43aa23fc81909d3361209996b9ec completed July 19, 2026, 3:25 a.m.
Created at: April 26, 2026, 8:19 p.m.