Triple

T409633
Position Surface form Disambiguated ID Type / Status
Subject London Euston E9460 entity
Predicate stationCode P1289 FINISHED
Object EUS
EUS is the three-letter National Rail station code for London Euston, a major central London railway terminus.
 E51945 NE FINISHED

How this triple was built (4 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: EUS | Statement: [London Euston, stationCode, EUS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: EUS
Context triple: [London Euston, stationCode, EUS]
  • A. Este
    Este is an ancient town in northern Italy notable as a key center of the Venetic civilization and culture.
  • B. HES
    HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
  • C. DSU
    DSU is the World Trade Organization’s legal framework that sets out the rules and procedures for resolving trade disputes between member countries.
  • D. FÜ
    FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
  • E. UAL
    UAL is the ICAO airline designator used to identify United Airlines in aviation operations and air traffic control.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: EUS
Triple: [London Euston, stationCode, EUS]
Generated description
EUS is the three-letter National Rail station code for London Euston, a major central London railway terminus.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: EUS
Target entity description: EUS is the three-letter National Rail station code for London Euston, a major central London railway terminus.
  • A. Este
    Este is an ancient town in northern Italy notable as a key center of the Venetic civilization and culture.
  • B. HES
    HES is the commonly used abbreviation for Historic Environment Scotland, the public body responsible for protecting and promoting Scotland’s historic environment.
  • C. DSU
    DSU is the World Trade Organization’s legal framework that sets out the rules and procedures for resolving trade disputes between member countries.
  • D. FÜ
    FÜ is the vehicle registration code used on license plates for the city of Fürth in Bavaria, Germany.
  • E. UAL
    UAL is the ICAO airline designator used to identify United Airlines in aviation operations and air traffic control.
  • F. None of above. chosen

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_69a2e80111fc8190961d5b7c6154123f completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2ecc098c4819088d127c5ea55ced9 completed Feb. 28, 2026, 1:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a41777d794819099a07555ad2defe2 completed March 1, 2026, 10:39 a.m.
NEDg Description generation batch_69a418da55088190935babe9abae5ac4 completed March 1, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_69a4196334948190a1f6004b1a292550 completed March 1, 2026, 10:48 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.