Triple

T24678849
Position Surface form Disambiguated ID Type / Status
Subject Lagodekhi Municipality E611066 entity
Predicate hasRiver P165 FINISHED
Object Lagodekhistskali River
The Lagodekhistskali River is a watercourse in eastern Georgia that flows through the Lagodekhi area of the Kakheti region, contributing to the local landscape and ecosystems.
E2272179 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: Lagodekhistskali River | Statement: [Lagodekhi Municipality, hasRiver, Lagodekhistskali 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: Lagodekhistskali River
Triple: [Lagodekhi Municipality, hasRiver, Lagodekhistskali River]
Generated description
The Lagodekhistskali River is a watercourse in eastern Georgia that flows through the Lagodekhi area of the Kakheti region, contributing to the local landscape 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_69e2c4d5c2dc8190ac857dea25ec6ce9 completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40fbe0b888190889cf9a529e84aac completed May 1, 2026, 2:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a41d62f66108190a932d74bafeeec41 completed June 29, 2026, 2:19 a.m.
NEDg Description generation batch_6a41d6d79f9c8190ab63069d374deddd completed June 29, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_6a41d72f88fc8190b5194d82e21e2da3 completed June 29, 2026, 2:23 a.m.
Created at: April 18, 2026, 3:08 a.m.