Triple

T15208800
Position Surface form Disambiguated ID Type / Status
Subject Letchworth Garden City railway station E363458 entity
Predicate hasStationCode P1289 FINISHED
Object LET
LET is the National Rail station code assigned to Letchworth Garden City railway station in Hertfordshire, England.
 E1143133 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: LET | Statement: [Letchworth Garden City railway station, hasStationCode, LET]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LET
Context triple: [Letchworth Garden City railway station, hasStationCode, LET]
  • A. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • B. LeT
    LeT is a Pakistan-based Islamist militant organization widely known for carrying out the 2008 Mumbai terrorist attacks and being designated as a terrorist group by numerous countries.
  • C. LE
    LE is the abbreviation for Les Engagés, a centrist political party in Belgium that emerged from the reform of the former Humanist Democratic Centre (cdH).
  • D. LT
    LT is the abbreviated name for the Logic Theorist, an early computer program that pioneered automated theorem proving in mathematical logic.
  • E. LT
    LT is a mid-level trim designation commonly used by Chevrolet to denote a better-equipped, more comfort- and feature-focused version of its vehicles.
  • 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: LET
Triple: [Letchworth Garden City railway station, hasStationCode, LET]
Generated description
LET is the National Rail station code assigned to Letchworth Garden City railway station in Hertfordshire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LET
Target entity description: LET is the National Rail station code assigned to Letchworth Garden City railway station in Hertfordshire, England.
  • A. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • B. LeT
    LeT is a Pakistan-based Islamist militant organization widely known for carrying out the 2008 Mumbai terrorist attacks and being designated as a terrorist group by numerous countries.
  • C. LE
    LE is the abbreviation for Les Engagés, a centrist political party in Belgium that emerged from the reform of the former Humanist Democratic Centre (cdH).
  • D. LT
    LT is a mid-level trim designation commonly used by Chevrolet to denote a better-equipped, more comfort- and feature-focused version of its vehicles.
  • E. LT
    LT is the abbreviated name for the Logic Theorist, an early computer program that pioneered automated theorem proving in mathematical logic.
  • 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e006b8e2788190bd1831762e4181ae completed April 15, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed33dbda08190a10ba81082d0d183 completed May 9, 2026, 6:25 a.m.
NEDg Description generation batch_69fed47c88d08190a4396b955c9bb388 completed May 9, 2026, 6:30 a.m.
NED2 Entity disambiguation (via description) batch_69fed50956408190b1426d578803974e completed May 9, 2026, 6:32 a.m.
Created at: April 10, 2026, 3:11 a.m.