Triple

T30217910
Position Surface form Disambiguated ID Type / Status
Subject Along E768257 entity
Predicate riverNearby P15504 FINISHED
Object Siyom River
The Siyom River is a tributary of the Brahmaputra River flowing through the Indian state of Arunachal Pradesh, known for its scenic valleys and largely untouched natural surroundings.
 E2295107 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: Siyom River | Statement: [Along, riverNearby, Siyom 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: Siyom River
Triple: [Along, riverNearby, Siyom River]
Generated description
The Siyom River is a tributary of the Brahmaputra River flowing through the Indian state of Arunachal Pradesh, known for its scenic valleys and largely untouched natural surroundings.

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_69f2247fd8b8819087fcf83cb7a05eb8 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f67ff6fdf481908bf368299814159b completed May 2, 2026, 10:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7d067e7bf881909a35a6752d7c71ec completed Aug. 12, 2026, 11:49 p.m.
NEDg Description generation batch_6a7d06ec01fc8190bb59ff1e8560a74e completed Aug. 12, 2026, 11:51 p.m.
NED2 Entity disambiguation (via description) batch_6a7d0976933481908c7e6bf4ec58d382 completed Aug. 13, 2026, 12:01 a.m.
Created at: April 29, 2026, 7:34 p.m.