Triple

T32301257
Position Surface form Disambiguated ID Type / Status
Subject M1 Junction 15 E825243 entity
Predicate servesCorridor P2566 FINISHED
Object Midlands–South East England route
The Midlands–South East England route is a major transport corridor linking the English Midlands with London and the South East, carrying significant long-distance and regional traffic.
 E2002843 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: Midlands–South East England route | Statement: [M1 Junction 15, servesCorridor, Midlands–South East England route]
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: Midlands–South East England route
Triple: [M1 Junction 15, servesCorridor, Midlands–South East England route]
Generated description
The Midlands–South East England route is a major transport corridor linking the English Midlands with London and the South East, carrying significant long-distance and regional traffic.

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_69f349115304819084ee91d345b6c8aa completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bd7481988190addeb1c9acd75386 completed May 3, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a30570cfd888190bfadf79c4cfcdb9b completed June 15, 2026, 7:48 p.m.
NEDg Description generation batch_6a31b9a482308190a82183f8bf571854 completed June 16, 2026, 9:01 p.m.
NED2 Entity disambiguation (via description) batch_6a33e21b231c8190860a4633feccc7fb completed June 18, 2026, 12:18 p.m.
Created at: May 1, 2026, 12:45 a.m.