Triple

T33555631
Position Surface form Disambiguated ID Type / Status
Subject Hamadan County E859463 entity
Predicate hasPart P35 FINISHED
Object Central District of Hamadan County
The Central District of Hamadan County is an administrative subdivision in Hamadan Province, Iran, encompassing the county’s capital city and its surrounding areas.
E2058182 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: Central District of Hamadan County | Statement: [Hamadan County, hasPart, Central District of Hamadan 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: Central District of Hamadan County
Triple: [Hamadan County, hasPart, Central District of Hamadan County]
Generated description
The Central District of Hamadan County is an administrative subdivision in Hamadan Province, Iran, encompassing the county’s capital city and its surrounding areas.

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_69f3497b2b68819093207971b5e13dc8 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6f70c17d88190aa74afc2dd2a0467 completed May 3, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35afd043bc81908de32e6fba232188 completed June 19, 2026, 9:08 p.m.
NEDg Description generation batch_6a35bc7e38bc819095d4dc3b8b63989b completed June 19, 2026, 10:02 p.m.
NED2 Entity disambiguation (via description) batch_6a35bce82dc48190aec3f2a804bf9a96 completed June 19, 2026, 10:04 p.m.
Created at: May 1, 2026, 1:40 a.m.