Triple

T29009086
Position Surface form Disambiguated ID Type / Status
Subject Armenia Alliance E736513 entity
Predicate keyFigure P256 FINISHED
Object Ishkhan Saghatelyan
Ishkhan Saghatelyan is an Armenian politician known for his leadership role in opposition movements and his prominent position within the Armenia Alliance.
E1864154 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: Ishkhan Saghatelyan | Statement: [Armenia Alliance, keyFigure, Ishkhan Saghatelyan]
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: Ishkhan Saghatelyan
Triple: [Armenia Alliance, keyFigure, Ishkhan Saghatelyan]
Generated description
Ishkhan Saghatelyan is an Armenian politician known for his leadership role in opposition movements and his prominent position within the Armenia Alliance.

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_69f077eb81e88190ad9ff62cbb9f555e completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f65fda92188190b20bfd59902ed27d completed May 2, 2026, 8:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25c0d0ed9881909e07de59b4f2c93d completed June 7, 2026, 7:04 p.m.
NEDg Description generation batch_6a25c4f14e108190a8e492f95a1af9b0 completed June 7, 2026, 7:22 p.m.
NED2 Entity disambiguation (via description) batch_6a25c93893f88190b77d1054320288dd completed June 7, 2026, 7:40 p.m.
Created at: April 28, 2026, 9:40 a.m.