Triple

T33983857
Position Surface form Disambiguated ID Type / Status
Subject Torpoint E871358 entity
Predicate hasSecondarySchool P3445 FINISHED
Object Torpoint Community College
Torpoint Community College is a coeducational secondary school and sixth form serving the town of Torpoint and surrounding areas in Cornwall, England.
E2077649 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: Torpoint Community College | Statement: [Torpoint, hasSecondarySchool, Torpoint Community College]
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: Torpoint Community College
Triple: [Torpoint, hasSecondarySchool, Torpoint Community College]
Generated description
Torpoint Community College is a coeducational secondary school and sixth form serving the town of Torpoint and surrounding areas in Cornwall, England.

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_69f3499e964c8190b674b03f6f791b4b completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7038c3d4c8190bf8d42c1bd1762a3 completed May 3, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3692dc1a948190bba6b5c7824a9a40 completed June 20, 2026, 1:17 p.m.
NEDg Description generation batch_6a3694ea32d48190bee74e8717d79e8e completed June 20, 2026, 1:26 p.m.
NED2 Entity disambiguation (via description) batch_6a3695dcf1748190b4a465bf69162128 completed June 20, 2026, 1:30 p.m.
Created at: May 1, 2026, 1:50 a.m.