Triple

T30391289
Position Surface form Disambiguated ID Type / Status
Subject Mile End Campus E773089 entity
Predicate hasBuilding P105 FINISHED
Object Francis Bancroft Building
The Francis Bancroft Building is a major academic and teaching facility located on Queen Mary University of London’s Mile End campus.
 E1914060 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: Francis Bancroft Building | Statement: [Mile End Campus, hasBuilding, Francis Bancroft 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: Francis Bancroft Building
Triple: [Mile End Campus, hasBuilding, Francis Bancroft Building]
Generated description
The Francis Bancroft Building is a major academic and teaching facility located on Queen Mary University of London’s Mile End campus.

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_69f2248ef0a48190aa54d4d8ac3e5758 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6859ceaa481908671a20b6cee0fca completed May 2, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2798a8c53c81909e68bde70085b2c3 completed June 9, 2026, 4:38 a.m.
NEDg Description generation batch_6a279b4477108190b3c2d60ab9ac5c15 completed June 9, 2026, 4:49 a.m.
NED2 Entity disambiguation (via description) batch_6a279ba7ee108190b856c41db2cc4b7e completed June 9, 2026, 4:50 a.m.
Created at: April 29, 2026, 8:02 p.m.