Triple

T33723693
Position Surface form Disambiguated ID Type / Status
Subject BC E864084 entity
Predicate jurisdiction P82 FINISHED
Object Bacău County authorities
Bacău County authorities are the local governmental and administrative bodies responsible for managing public services, development, and governance within Bacău County in Romania.
E2063315 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: Bacău County authorities | Statement: [BC, jurisdiction, Bacău County authorities]
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: Bacău County authorities
Triple: [BC, jurisdiction, Bacău County authorities]
Generated description
Bacău County authorities are the local governmental and administrative bodies responsible for managing public services, development, and governance within Bacău County in 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_69f34989871c81908682e22a2fe4b829 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6faef878881909dca8cb225e687cb completed May 3, 2026, 7:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a363caf51808190973f40beaf09a6c0 completed June 20, 2026, 7:09 a.m.
NEDg Description generation batch_6a364231c17881908ce7a2c3753504ab completed June 20, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_6a3642bc3dac8190a1302ea789bd716c completed June 20, 2026, 7:35 a.m.
Created at: May 1, 2026, 1:44 a.m.