Triple

T26515835
Position Surface form Disambiguated ID Type / Status
Subject UCL Main Quad E669809 entity
Predicate surroundedBy P224 FINISHED
Object UCL Pearson Building
The UCL Pearson Building is a historic academic building on University College London’s Bloomsbury campus, housing teaching and administrative facilities and forming part of the university’s central quadrangle complex.
E1762266 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: UCL Pearson Building | Statement: [UCL Main Quad, surroundedBy, UCL Pearson Building]
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: UCL Pearson Building
Triple: [UCL Main Quad, surroundedBy, UCL Pearson Building]
Generated description
The UCL Pearson Building is a historic academic building on University College London’s Bloomsbury campus, housing teaching and administrative facilities and forming part of the university’s central quadrangle complex.

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_69eeb31b6dcc8190b30632dc3928a0c0 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613bd3f308190a936e670bf8a1b4e completed May 2, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12535a16e48190bdfe798f281fd4ec completed May 24, 2026, 1:24 a.m.
NEDg Description generation batch_6a12574c06788190951ce13779ea5ba8 completed May 24, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_6a125793327881908c67b67f1bdf19e6 completed May 24, 2026, 1:42 a.m.
Created at: April 27, 2026, 1:23 a.m.