Triple

T21315462
Position Surface form Disambiguated ID Type / Status
Subject St Martin’s Lane E525457 entity
Predicate hasJunctionWith P1018 FINISHED
Object William IV Street
William IV Street is a central London street in the City of Westminster, linking the Strand area with Charing Cross and known for its shops, restaurants, and proximity to major West End attractions.
 E1763148 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: William IV Street | Statement: [St Martin’s Lane, hasJunctionWith, William IV Street]
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: William IV Street
Triple: [St Martin’s Lane, hasJunctionWith, William IV Street]
Generated description
William IV Street is a central London street in the City of Westminster, linking the Strand area with Charing Cross and known for its shops, restaurants, and proximity to major West End attractions.

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_69e0b51ad810819098c12392c8e55f6c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e75dcf2534819097abbb2e9559e791 completed April 21, 2026, 11:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a126239807881908843eaced3181240 completed May 24, 2026, 2:28 a.m.
NEDg Description generation batch_6a12667d95ec8190900555e50d903e5d completed May 24, 2026, 2:46 a.m.
NED2 Entity disambiguation (via description) batch_6a1266dd3b748190a06a76a7587eff99 completed May 24, 2026, 2:47 a.m.
Created at: April 16, 2026, 4:28 p.m.