Triple

T37354578
Position Surface form Disambiguated ID Type / Status
Subject Bates-Hendricks, Indianapolis E927417 entity
Predicate fireProtection P8978 FINISHED
Object Indianapolis Fire Department
The Indianapolis Fire Department is the municipal agency responsible for providing fire suppression, emergency medical services, and rescue operations throughout Indianapolis, Indiana.
E2224967 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: Indianapolis Fire Department | Statement: [Bates-Hendricks, Indianapolis, fireProtection, Indianapolis 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: Indianapolis Fire Department
Triple: [Bates-Hendricks, Indianapolis, fireProtection, Indianapolis Fire Department]
Generated description
The Indianapolis Fire Department is the municipal agency responsible for providing fire suppression, emergency medical services, and rescue operations throughout Indianapolis, Indiana.

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_69f76eb5e034819088e53ab5b7909a68 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5bc312c88190989761c6dd48a961 completed May 6, 2026, 3:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4076f093f08190a92287385694632e completed June 28, 2026, 1:20 a.m.
NEDg Description generation batch_6a4077c183048190b60204779b4336b5 completed June 28, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_6a4078362d0881909b963ee3fe45787e completed June 28, 2026, 1:26 a.m.
Created at: May 3, 2026, 4:16 p.m.