Triple

T33147637
Position Surface form Disambiguated ID Type / Status
Subject Park Street, Cambridge E848345 entity
Predicate hasNearby P350 FINISHED
Object Thompson’s Lane
Thompson’s Lane is a small street in central Cambridge, England, known for its proximity to the River Cam, historic colleges, and local churches.
 E2295145 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: Thompson’s Lane | Statement: [Park Street, Cambridge, hasNearby, Thompson’s Lane]
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: Thompson’s Lane
Triple: [Park Street, Cambridge, hasNearby, Thompson’s Lane]
Generated description
Thompson’s Lane is a small street in central Cambridge, England, known for its proximity to the River Cam, historic colleges, and local churches.

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_69f3495a458c8190a1d34b237ba0be3f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d88ffa6081909b64a7014108abc7 completed May 3, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7d0e8273bc81908ac22dad43b96416 completed Aug. 13, 2026, 12:23 a.m.
NEDg Description generation batch_6a7d0ee871e88190bb47b34077056658 completed Aug. 13, 2026, 12:25 a.m.
NED2 Entity disambiguation (via description) batch_6a7d0f5af2648190b7891ec94db6a8fe completed Aug. 13, 2026, 12:27 a.m.
Created at: May 1, 2026, 1:28 a.m.