Triple

T24512166
Position Surface form Disambiguated ID Type / Status
Subject Leszno County (city county) E606253 entity
Predicate headOfGovernment P307 FINISHED
Object Mayor of Leszno
The Mayor of Leszno is the chief executive official responsible for governing the city of Leszno in west-central Poland, overseeing local administration, public services, and municipal development.
E1638134 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: Mayor of Leszno | Statement: [Leszno County (city county), headOfGovernment, Mayor of Leszno]
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: Mayor of Leszno
Triple: [Leszno County (city county), headOfGovernment, Mayor of Leszno]
Generated description
The Mayor of Leszno is the chief executive official responsible for governing the city of Leszno in west-central Poland, overseeing local administration, public services, and municipal development.

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_69e2c4c725148190a4e41577c5cb409c completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a84d3da08190bfb7805cea1525d1 completed April 30, 2026, 12:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee8f9da881908d1756de8761fb2e completed May 22, 2026, 5:50 a.m.
NEDg Description generation batch_6a0fef20efe08190bb4cb412e2473ae5 completed May 22, 2026, 5:52 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff097dd8881908bb83d84a6581ef7 completed May 22, 2026, 5:58 a.m.
Created at: April 18, 2026, 2:24 a.m.