Triple

T25099674
Position Surface form Disambiguated ID Type / Status
Subject London water supply system E628687 entity
Predicate includesTreatmentWorks P172078 FINISHED
Object Hornsey Water Treatment Works
Hornsey Water Treatment Works is a major water treatment facility in London that processes and supplies potable water as part of the city's public water infrastructure.
E1682051 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: Hornsey Water Treatment Works | Statement: [London water supply system, includesTreatmentWorks, Hornsey Water Treatment Works]
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: Hornsey Water Treatment Works
Triple: [London water supply system, includesTreatmentWorks, Hornsey Water Treatment Works]
Generated description
Hornsey Water Treatment Works is a major water treatment facility in London that processes and supplies potable water as part of the city's public water infrastructure.

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_69e2ff3071548190b62d1ac237397197 completed April 18, 2026, 3:49 a.m.
NER Named-entity recognition batch_69f6aa232a5c8190bd09a96cdc552c7a completed May 3, 2026, 1:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad3714788190abbc5ead47b2bd09 completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10ae56b8a48190a448e1a4bd938a2b completed May 22, 2026, 7:28 p.m.
NED2 Entity disambiguation (via description) batch_6a10af2b626081908a1a67773654a991 completed May 22, 2026, 7:31 p.m.
Created at: April 18, 2026, 6:25 a.m.