Triple

T27378650
Position Surface form Disambiguated ID Type / Status
Subject Springfield, New Jersey E691149 entity
Predicate hasEmergencyService P464 FINISHED
Object Springfield Fire Department
The Springfield Fire Department is the municipal fire and emergency response agency serving the community of Springfield, New Jersey.
 E1770771 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: Springfield Fire Department | Statement: [Springfield, New Jersey, hasEmergencyService, Springfield Fire 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: Springfield Fire Department
Triple: [Springfield, New Jersey, hasEmergencyService, Springfield Fire Department]
Generated description
The Springfield Fire Department is the municipal fire and emergency response agency serving the community of Springfield, New Jersey.

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_69ef52022538819081f873d0c84a6dd6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62c84610481909e65995538e8faea completed May 2, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12a7ea16ec8190859b125d02fdfc56 completed May 24, 2026, 7:25 a.m.
NEDg Description generation batch_6a12a9369fb081909cf7728dcb943585 completed May 24, 2026, 7:31 a.m.
NED2 Entity disambiguation (via description) batch_6a12aa0e55a88190ae8b69a3063f47a7 completed May 24, 2026, 7:34 a.m.
Created at: April 27, 2026, 12:21 p.m.