Triple

T26848980
Position Surface form Disambiguated ID Type / Status
Subject Taşkent, Konya, Turkey E676002 entity
Predicate governedBy P46 FINISHED
Object Taşkent District Governorate
Taşkent District Governorate is the local administrative authority responsible for governing the Taşkent district in Konya Province, Turkey.
E1743266 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: Taşkent District Governorate | Statement: [Taşkent, Konya, Turkey, governedBy, Taşkent District Governorate]
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: Taşkent District Governorate
Triple: [Taşkent, Konya, Turkey, governedBy, Taşkent District Governorate]
Generated description
Taşkent District Governorate is the local administrative authority responsible for governing the Taşkent district in Konya Province, Turkey.

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_69eee9b8d5e88190a07d3455c0fbb21f completed April 27, 2026, 4:44 a.m.
NER Named-entity recognition batch_69f61b90393c819090595eac8e538e05 completed May 2, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12134f7150819081ab4f40ea6eb610 completed May 23, 2026, 8:51 p.m.
NEDg Description generation batch_6a12150278448190b2538abe4f8d2e6f completed May 23, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1215e830648190afc5de590a2a2cc1 completed May 23, 2026, 9:02 p.m.
Created at: April 27, 2026, 5:14 a.m.