Triple

T29455649
Position Surface form Disambiguated ID Type / Status
Subject National Assembly Building, Yerevan E747090 entity
Predicate hasNameInEnglish P3437 FINISHED
Object National Assembly Building
The National Assembly Building is the official seat of Armenia’s legislative body, located in the capital city of Yerevan.
E1866105 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: National Assembly Building | Statement: [National Assembly Building, Yerevan, hasNameInEnglish, National Assembly Building]
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: National Assembly Building
Triple: [National Assembly Building, Yerevan, hasNameInEnglish, National Assembly Building]
Generated description
The National Assembly Building is the official seat of Armenia’s legislative body, located in the capital city of Yerevan.

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_69f0a7a230488190b44a97fe3d16f731 completed April 28, 2026, 12:27 p.m.
NER Named-entity recognition batch_69f66b6c26a481908018e663aee7b269 completed May 2, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25d943166481909430879014e1c02a completed June 7, 2026, 8:49 p.m.
NEDg Description generation batch_6a25dcffa7b481908d59b0da4dc1fa7c completed June 7, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_6a25e0dc908c8190a3d1b875d35bee66 completed June 7, 2026, 9:21 p.m.
Created at: April 28, 2026, 3:36 p.m.