Triple

T24996385
Position Surface form Disambiguated ID Type / Status
Subject Pancras Square E625578 entity
Predicate hasBuilding P105 FINISHED
Object Four Pancras Square
Four Pancras Square is a contemporary office building in the King’s Cross redevelopment area of London, known for its modern design and role in the Pancras Square business district.
 E1669627 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: Four Pancras Square | Statement: [Pancras Square, hasBuilding, Four Pancras Square]
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: Four Pancras Square
Triple: [Pancras Square, hasBuilding, Four Pancras Square]
Generated description
Four Pancras Square is a contemporary office building in the King’s Cross redevelopment area of London, known for its modern design and role in the Pancras Square business district.

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_69e2ff2611c081908710457fbe6d376b completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f44a4b309881908bab784bfccfc6f7 completed May 1, 2026, 6:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1067ae505881909e88eca304e74c2e completed May 22, 2026, 2:26 p.m.
NEDg Description generation batch_6a106844f694819082bb12621dcb700b completed May 22, 2026, 2:29 p.m.
NED2 Entity disambiguation (via description) batch_6a1068b5f1048190a4ff23ddfd76abd6 completed May 22, 2026, 2:31 p.m.
Created at: April 18, 2026, 6:04 a.m.