Triple

T33541940
Position Surface form Disambiguated ID Type / Status
Subject Thodupuzha E859093 entity
Predicate namedAfter P63 FINISHED
Object Thodupuzha River
Thodupuzha River is a river in the Idukki district of Kerala, India, known for flowing through the town of Thodupuzha and contributing to the region’s agriculture and ecology.
E2112537 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: Thodupuzha River | Statement: [Thodupuzha, namedAfter, Thodupuzha 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: Thodupuzha River
Triple: [Thodupuzha, namedAfter, Thodupuzha River]
Generated description
Thodupuzha River is a river in the Idukki district of Kerala, India, known for flowing through the town of Thodupuzha and contributing to the region’s agriculture and ecology.

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_69f3497a5be08190a39b12736899e034 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f6c4f8748190a3f38046cacc1f9d completed May 3, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a376f83b46c81909acd9b0d135dbc6e completed June 21, 2026, 4:58 a.m.
NEDg Description generation batch_6a376ff513648190a3fa8ef93765fd2f completed June 21, 2026, 5 a.m.
NED2 Entity disambiguation (via description) batch_6a377056e3f8819087c206896eaeab07 completed June 21, 2026, 5:02 a.m.
Created at: May 1, 2026, 1:39 a.m.