Triple

T25543414
Position Surface form Disambiguated ID Type / Status
Subject Potters Bar railway station E640231 entity
Predicate hasEvent P811 FINISHED
Object Potters Bar rail crash 2002
The Potters Bar rail crash 2002 was a fatal train derailment in Hertfordshire, England, caused by faulty track maintenance, which led to multiple deaths and injuries and prompted major rail safety investigations.
E1685333 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: Potters Bar rail crash 2002 | Statement: [Potters Bar railway station, hasEvent, Potters Bar rail crash 2002]
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: Potters Bar rail crash 2002
Triple: [Potters Bar railway station, hasEvent, Potters Bar rail crash 2002]
Generated description
The Potters Bar rail crash 2002 was a fatal train derailment in Hertfordshire, England, caused by faulty track maintenance, which led to multiple deaths and injuries and prompted major rail safety investigations.

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_69e75dbfff7081909b0aa779d48321d2 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f895e458819081cf031b70d20e56 completed May 2, 2026, 1:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad97c1ac8190b5d2ae6ef8c0f6ec completed May 22, 2026, 7:25 p.m.
NEDg Description generation batch_6a10af55080c8190be4f15abd7f0dc54 completed May 22, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a10b003abe48190b31afc7ee2352d06 completed May 22, 2026, 7:35 p.m.
Created at: April 21, 2026, 3:27 p.m.