Triple

T27072620
Position Surface form Disambiguated ID Type / Status
Subject Burt Township government E685369 entity
Predicate hasOfficer P537 FINISHED
Object Burt Township Treasurer
The Burt Township Treasurer is the local elected official responsible for managing the township’s finances, including collecting taxes, safeguarding funds, and overseeing disbursements.
E1756105 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: Burt Township Treasurer | Statement: [Burt Township government, hasOfficer, Burt Township Treasurer]
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: Burt Township Treasurer
Triple: [Burt Township government, hasOfficer, Burt Township Treasurer]
Generated description
The Burt Township Treasurer is the local elected official responsible for managing the township’s finances, including collecting taxes, safeguarding funds, and overseeing disbursements.

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_69ef14843b1481909d828b3d5a44550a completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f6231257f481909d576c19559e0ad0 completed May 2, 2026, 4:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1247fc10088190a97eca7ef293ba39 completed May 24, 2026, 12:36 a.m.
NEDg Description generation batch_6a12488822208190aab1355ac3efd2a6 completed May 24, 2026, 12:38 a.m.
NED2 Entity disambiguation (via description) batch_6a124935c01c8190b9d6d13c4f50a104 completed May 24, 2026, 12:41 a.m.
Created at: April 27, 2026, 8:29 a.m.