Triple

T32755550
Position Surface form Disambiguated ID Type / Status
Subject Provincial Commissioner (before 2010) E837610 entity
Predicate usedTitle P3254 FINISHED
Object Provincial Commissioner
The Provincial Commissioner is a senior regional leadership role, typically overseeing administration, governance, or policing within a province.
E2021471 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: Provincial Commissioner | Statement: [Provincial Commissioner (before 2010), usedTitle, Provincial Commissioner]
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: Provincial Commissioner
Triple: [Provincial Commissioner (before 2010), usedTitle, Provincial Commissioner]
Generated description
The Provincial Commissioner is a senior regional leadership role, typically overseeing administration, governance, or policing within a province.

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_69f34937f97c8190b7f84bea045df3ae completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6cce0ce6c8190aca71392382ec09f completed May 3, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34a7bc3e308190a6ee32259cda442b completed June 19, 2026, 2:21 a.m.
NEDg Description generation batch_6a34a8fb2e0081908cdac2a172ea5c32 completed June 19, 2026, 2:27 a.m.
NED2 Entity disambiguation (via description) batch_6a34a9cef0248190bf3bef6627945496 completed June 19, 2026, 2:30 a.m.
Created at: May 1, 2026, 1:12 a.m.