Triple

T30772733
Position Surface form Disambiguated ID Type / Status
Subject Parsabad E783570 entity
Predicate locatedInAdministrativeTerritorialEntity P40 FINISHED
Object Parsabad County
Parsabad County is an administrative division in Ardabil Province in northwestern Iran, known for its agricultural activities and location near the border with Azerbaijan.
E1930280 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: Parsabad County | Statement: [Parsabad, locatedInAdministrativeTerritorialEntity, Parsabad 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: Parsabad County
Triple: [Parsabad, locatedInAdministrativeTerritorialEntity, Parsabad County]
Generated description
Parsabad County is an administrative division in Ardabil Province in northwestern Iran, known for its agricultural activities and location near the border with Azerbaijan.

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_69f224b1519081908b9db003fd2073e0 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68fc34b848190925e29fa4756f97d completed May 2, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28b09c62ec8190b608007907f79bc9 completed June 10, 2026, 12:32 a.m.
NEDg Description generation batch_6a28b1b3d41481908b42370b7ad16ba4 completed June 10, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_6a28b2561d808190b5fbfc96e46634df completed June 10, 2026, 12:39 a.m.
Created at: April 29, 2026, 8:40 p.m.