Triple

T35519091
Position Surface form Disambiguated ID Type / Status
Subject Baker, Louisiana E1026502 entity
Predicate hasLawEnforcement P13246 FINISHED
Object Baker Police Department
The Baker Police Department is the municipal law enforcement agency responsible for maintaining public safety and enforcing laws within the city limits of Baker, Louisiana.
E2144691 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: Baker Police Department | Statement: [Baker, Louisiana, hasLawEnforcement, Baker Police Department]
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: Baker Police Department
Triple: [Baker, Louisiana, hasLawEnforcement, Baker Police Department]
Generated description
The Baker Police Department is the municipal law enforcement agency responsible for maintaining public safety and enforcing laws within the city limits of Baker, Louisiana.

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_69f76dfe78b081908e2b14cb88dd8c00 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7979ecfe0819099e7fd77e588b8b8 completed May 3, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a384a3ea2588190b470f8493b0bcbb9 completed June 21, 2026, 8:31 p.m.
NEDg Description generation batch_6a384ad781b48190b37e3ae4708eae57 completed June 21, 2026, 8:34 p.m.
NED2 Entity disambiguation (via description) batch_6a384b6c05ec8190b41e56814b5bf7c0 completed June 21, 2026, 8:37 p.m.
Created at: May 3, 2026, 4:04 p.m.