Triple

T33623169
Position Surface form Disambiguated ID Type / Status
Subject Rahimabad Garden E861326 entity
Predicate locatedIn P40 FINISHED
Object Birjand County
Birjand County is an administrative region in South Khorasan Province in eastern Iran, known for its historical gardens, traditional architecture, and role as a regional cultural and economic center.
E2063367 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: Birjand County | Statement: [Rahimabad Garden, locatedIn, Birjand County]
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: Birjand County
Triple: [Rahimabad Garden, locatedIn, Birjand County]
Generated description
Birjand County is an administrative region in South Khorasan Province in eastern Iran, known for its historical gardens, traditional architecture, and role as a regional cultural and economic center.

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_69f34980fabc81909819228729a9ca84 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f81ea9388190bf58dad0672e7697 completed May 3, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363c83dd808190b74a7ded2b52aff9 completed June 20, 2026, 7:08 a.m.
NEDg Description generation batch_6a36462f32e081908f82f4b58675c5e4 completed June 20, 2026, 7:50 a.m.
NED2 Entity disambiguation (via description) batch_6a3647777e448190a89f88f48861ef5d completed June 20, 2026, 7:55 a.m.
Created at: May 1, 2026, 1:41 a.m.