Triple

T7993643
Position Surface form Disambiguated ID Type / Status
Subject Syon Lane railway station E186068 entity
Predicate hasStationCode P1289 FINISHED
Object SYL
SYL is the National Rail station code for Syon Lane railway station in west London, England.
 E703779 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: SYL | Statement: [Syon Lane railway station, hasStationCode, SYL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SYL
Context triple: [Syon Lane railway station, hasStationCode, SYL]
  • A. SYR
    SYR is the three-letter ISO 3166-1 alpha-3 country code representing the Middle Eastern nation of Syria.
  • B. SILE
    SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
  • C. SY
    SY is a UK postcode area covering Shrewsbury and surrounding parts of Shropshire and nearby counties in western England and the Welsh border region.
  • D. SYP
    SYP is the ISO 4217 currency code for the Syrian pound, the official monetary unit of Syria.
  • E. Sy
    Sy is a Diameter-based interface in telecommunications networks used for policy and charging control between the PCRF and online charging systems.
  • 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: SYL
Triple: [Syon Lane railway station, hasStationCode, SYL]
Generated description
SYL is the National Rail station code for Syon Lane railway station in west London, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SYL
Target entity description: SYL is the National Rail station code for Syon Lane railway station in west London, England.
  • A. SYR
    SYR is the three-letter ISO 3166-1 alpha-3 country code representing the Middle Eastern nation of Syria.
  • B. SILE
    SILE is a modern typesetting system and document processor designed as a more flexible, programmable successor to traditional TeX-based workflows.
  • C. SY
    SY is a UK postcode area covering Shrewsbury and surrounding parts of Shropshire and nearby counties in western England and the Welsh border region.
  • D. SYP
    SYP is the ISO 4217 currency code for the Syrian pound, the official monetary unit of Syria.
  • E. Sy
    Sy is a Diameter-based interface in telecommunications networks used for policy and charging control between the PCRF and online charging systems.
  • 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_69ca829c6c308190ab05b43d234c52b2 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3c729afc81909d477b1623ac3f9d completed March 31, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0fe312c81908c6874fa0aabe7d5 completed March 31, 2026, 2:58 p.m.
NEDg Description generation batch_69cbe440a66c8190a5d5b417fb5082b7 completed March 31, 2026, 3:12 p.m.
NED2 Entity disambiguation (via description) batch_69cc338a1c48819086ece073e04e8fa6 completed March 31, 2026, 8:50 p.m.
Created at: March 30, 2026, 5:16 p.m.