Triple

T38388782
Position Surface form Disambiguated ID Type / Status
Subject Sânnicolau Mare E899652 entity
Predicate administeredBy P86 FINISHED
Object Timiș County Council
Timiș County Council is the local governing body responsible for regional administration, development, and public services across Timiș County in western Romania.
E2267846 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: Timiș County Council | Statement: [Sânnicolau Mare, administeredBy, Timiș County Council]
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: Timiș County Council
Triple: [Sânnicolau Mare, administeredBy, Timiș County Council]
Generated description
Timiș County Council is the local governing body responsible for regional administration, development, and public services across Timiș County in western Romania.

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_69f76e5c9b808190b486523f5c2f817d completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fccd1e84d08190b881f974c064e53b completed May 7, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b2acf9f08190a8334729b9df8665 completed June 28, 2026, 11:47 p.m.
NEDg Description generation batch_6a41b3ce800c8190868c4c9ad51282bd completed June 28, 2026, 11:52 p.m.
NED2 Entity disambiguation (via description) batch_6a41b4aff75081909d0946a1c0992447 completed June 28, 2026, 11:56 p.m.
Created at: May 3, 2026, 4:31 p.m.