Triple

T18915875
Position Surface form Disambiguated ID Type / Status
Subject Moorgate (street) E462722 entity
Predicate hasJunctionWith P1018 FINISHED
Object Ropemaker Street
Ropemaker Street is a street in the City of London’s financial district, known for its modern office buildings and proximity to Moorgate.
 E1815753 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: Ropemaker Street | Statement: [Moorgate (street), hasJunctionWith, Ropemaker 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: Ropemaker Street
Triple: [Moorgate (street), hasJunctionWith, Ropemaker Street]
Generated description
Ropemaker Street is a street in the City of London’s financial district, known for its modern office buildings and proximity to Moorgate.

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_69d8dcfdbbb881909964fa5a75bd0b48 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5c62685408190b17280147e1c247a completed April 20, 2026, 6:22 a.m.
NED1 Entity disambiguation (via context triple) batch_6a1632ce645881908eb118bc619c39ae completed May 26, 2026, 11:54 p.m.
NEDg Description generation batch_6a163388462481909f4ea41cb85696b0 completed May 26, 2026, 11:58 p.m.
NED2 Entity disambiguation (via description) batch_6a1633fc869c8190b6fe8595859de273 completed May 26, 2026, 11:59 p.m.
Created at: April 10, 2026, 11:58 a.m.