Triple

T30881621
Position Surface form Disambiguated ID Type / Status
Subject Khojavend District E786629 entity
Predicate capital P234 FINISHED
Object Khojavend
Khojavend is a town in the disputed Nagorno-Karabakh region, historically serving as an administrative center and often associated with the broader territorial conflict between Armenia and Azerbaijan.
E405041 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: Khojavend | Statement: [Khojavend District, capital, Khojavend]
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: Khojavend
Triple: [Khojavend District, capital, Khojavend]
Generated description
Khojavend is a town in the disputed Nagorno-Karabakh region, historically serving as an administrative center and often associated with the broader territorial conflict between Armenia and Azerbaijan.

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_69f224bae17c8190bb3a6a28e3d019df completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6920337108190be9cbe5d90986f5c completed May 3, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28c7e1e8808190931d2102436f688d completed June 10, 2026, 2:11 a.m.
NEDg Description generation batch_6a28c9c04c908190a05a6033553993de completed June 10, 2026, 2:19 a.m.
NED2 Entity disambiguation (via description) batch_6a28ca3922388190bf3e17b5e78ce781 completed June 10, 2026, 2:21 a.m.
Created at: April 29, 2026, 8:48 p.m.