Triple

T21184459
Position Surface form Disambiguated ID Type / Status
Subject Chuy River E522042 entity
Predicate hasTributary P415 FINISHED
Object Kara-Balta River
The Kara-Balta River is a mountain river in Kyrgyzstan that flows through the Chüy Region and supports local agriculture and settlements before joining the Chuy River.
E2087038 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: Kara-Balta River | Statement: [Chuy River, hasTributary, Kara-Balta 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: Kara-Balta River
Triple: [Chuy River, hasTributary, Kara-Balta River]
Generated description
The Kara-Balta River is a mountain river in Kyrgyzstan that flows through the Chüy Region and supports local agriculture and settlements before joining the Chuy River.

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_69e0b50ef1d48190b063aa342667df22 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e730205ce88190b0bb33003295d6e7 completed April 21, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36d5bc2318819092b8a32b3af63d72 completed June 20, 2026, 6:02 p.m.
NEDg Description generation batch_6a36d69820ac8190a102919d7bfbbeeb completed June 20, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_6a36d733c79c819099c6c8306ac9a7bd completed June 20, 2026, 6:08 p.m.
Created at: April 16, 2026, 3:06 p.m.