Triple

T30270612
Position Surface form Disambiguated ID Type / Status
Subject Royal Over-Seas League E769782 entity
Predicate hasClubhouse P4719 FINISHED
Object Over-Seas House, London
Over-Seas House, London is the central clubhouse and headquarters of the Royal Over-Seas League, located in central London and used for member accommodation, events, and social functions.
E1908855 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: Over-Seas House, London | Statement: [Royal Over-Seas League, hasClubhouse, Over-Seas House, London]
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: Over-Seas House, London
Triple: [Royal Over-Seas League, hasClubhouse, Over-Seas House, London]
Generated description
Over-Seas House, London is the central clubhouse and headquarters of the Royal Over-Seas League, located in central London and used for member accommodation, events, and social functions.

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_69f224856d9881908c7f0dd64f059672 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680d43c708190a28635b6f09d3895 completed May 2, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276ef65d3c81909481ad44da61757e completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a276fd755b08190b6b6ef8d78b455aa completed June 9, 2026, 1:43 a.m.
NED2 Entity disambiguation (via description) batch_6a2771970b548190ae6a535834242983 completed June 9, 2026, 1:51 a.m.
Created at: April 29, 2026, 7:43 p.m.