Triple

T35965632
Position Surface form Disambiguated ID Type / Status
Subject Tayside Fire and Rescue E1040134 entity
Predicate precededBy P97 FINISHED
Object Tayside Fire Brigade
Tayside Fire Brigade was the former regional fire and rescue service responsible for firefighting and emergency response in the Tayside area of Scotland before its reorganization into Tayside Fire and Rescue.
E1040134 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: Tayside Fire Brigade | Statement: [Tayside Fire and Rescue, precededBy, Tayside Fire Brigade]
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: Tayside Fire Brigade
Triple: [Tayside Fire and Rescue, precededBy, Tayside Fire Brigade]
Generated description
Tayside Fire Brigade was the former regional fire and rescue service responsible for firefighting and emergency response in the Tayside area of Scotland before its reorganization into Tayside Fire and Rescue.

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_69f76e26b21081909fd9ffb3aff6c77a completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7abfc14b481908ab27e625c9208eb completed May 3, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39dbb51aac8190923e7fbc07a606e5 completed June 23, 2026, 1:04 a.m.
NEDg Description generation batch_6a39dc6faffc8190bc65e812b89dffda completed June 23, 2026, 1:07 a.m.
NED2 Entity disambiguation (via description) batch_6a39dd3627f48190a70cd2c7a8497aa9 completed June 23, 2026, 1:11 a.m.
Created at: May 3, 2026, 4:07 p.m.