Triple

T28607432
Position Surface form Disambiguated ID Type / Status
Subject Kentron District, Yerevan E724089 entity
Predicate contains P35 FINISHED
Object Circular Park, Yerevan
Circular Park, Yerevan is a prominent green belt and recreational area encircling part of central Yerevan, known for its tree-lined walkways, monuments, and public gathering spaces.
E1829717 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: Circular Park, Yerevan | Statement: [Kentron District, Yerevan, contains, Circular Park, Yerevan]
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: Circular Park, Yerevan
Triple: [Kentron District, Yerevan, contains, Circular Park, Yerevan]
Generated description
Circular Park, Yerevan is a prominent green belt and recreational area encircling part of central Yerevan, known for its tree-lined walkways, monuments, and public gathering spaces.

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_69f01d816d7c8190a1fe27e3434041dc completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6521a1de48190919076ab91afc834 completed May 2, 2026, 7:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1ccf345b3c8190b6d26ff2eb2b99f4 completed June 1, 2026, 12:15 a.m.
NEDg Description generation batch_6a1ccff86fc88190b1438e77f3a5f101 completed June 1, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_6a24945efab88190a4ccb8a92331e469 completed June 6, 2026, 9:42 p.m.
Created at: April 28, 2026, 4:28 a.m.