Triple

T38566965
Position Surface form Disambiguated ID Type / Status
Subject Gorlovka E928248 entity
Predicate hasHigherEducationInstitution P113 FINISHED
Object Horlivka Institute for Foreign Languages
Horlivka Institute for Foreign Languages is a Ukrainian higher education institution specializing in the study and teaching of foreign languages.
E2275008 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: Horlivka Institute for Foreign Languages | Statement: [Gorlovka, hasHigherEducationInstitution, Horlivka Institute for Foreign Languages]
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: Horlivka Institute for Foreign Languages
Triple: [Gorlovka, hasHigherEducationInstitution, Horlivka Institute for Foreign Languages]
Generated description
Horlivka Institute for Foreign Languages is a Ukrainian higher education institution specializing in the study and teaching of foreign languages.

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_69f76eb8d1808190a588af29d8b266d6 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fcd90b04b0819094913c584479f107 completed May 7, 2026, 6:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41e0478fb08190bf3c1ba5f59a56ae completed June 29, 2026, 3:02 a.m.
NEDg Description generation batch_6a41e259cb5881908448f8159262a09f completed June 29, 2026, 3:11 a.m.
NED2 Entity disambiguation (via description) batch_6a41e2bf2724819096eb210e4430f2ac completed June 29, 2026, 3:13 a.m.
Created at: May 3, 2026, 4:32 p.m.