Triple

T24422020
Position Surface form Disambiguated ID Type / Status
Subject Castle Street (Cambridge) E615748 entity
Predicate hasJunctionWith P1018 FINISHED
Object Northampton Street (Cambridge)
Northampton Street is a central Cambridge road known for linking key city routes near the historic core and providing access to nearby colleges and local amenities.
 E1639707 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: Northampton Street (Cambridge) | Statement: [Castle Street (Cambridge), hasJunctionWith, Northampton Street (Cambridge)]
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: Northampton Street (Cambridge)
Triple: [Castle Street (Cambridge), hasJunctionWith, Northampton Street (Cambridge)]
Generated description
Northampton Street is a central Cambridge road known for linking key city routes near the historic core and providing access to nearby colleges and local amenities.

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_69e2d7eadb248190a867130fe45f0388 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f296a34d3081908d6099365e2e4046 completed April 29, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fee69a29881909e6cbc53ba544a0f completed May 22, 2026, 5:49 a.m.
NEDg Description generation batch_6a0ff2a66cf08190ad3724f56a0fe84f completed May 22, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_6a0ff34de0708190ab6f3e978b5feab7 completed May 22, 2026, 6:10 a.m.
Created at: April 18, 2026, 2:14 a.m.