Triple

T6766677
Position Surface form Disambiguated ID Type / Status
Subject Frimley railway station E154736 entity
Predicate stationCode P1289 FINISHED
Object FML
FML is the National Rail station code for Frimley railway station in Surrey, England.
 E617607 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: FML | Statement: [Frimley railway station, stationCode, FML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: FML
Context triple: [Frimley railway station, stationCode, FML]
  • A. FML
    FML is a moody, introspective Kanye West song from *The Life of Pablo* that explores emotional turmoil, relationships, and mental health over dark, atmospheric production.
  • B. FL
    FL is the standard two-letter United States Postal Service abbreviation for the state of Florida.
  • C. FL
    FL is the international vehicle registration code for the Principality of Liechtenstein.
  • D. FC
    FC is the standard abbreviation for Fibre Channel, a high-speed network technology primarily used to connect computer data storage in storage area networks.
  • E. FC
    FC is the vehicle registration and administrative code used to identify the Italian province of Forlì-Cesena.
  • 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: FML
Triple: [Frimley railway station, stationCode, FML]
Generated description
FML is the National Rail station code for Frimley railway station in Surrey, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: FML
Target entity description: FML is the National Rail station code for Frimley railway station in Surrey, England.
  • A. FML
    FML is a moody, introspective Kanye West song from *The Life of Pablo* that explores emotional turmoil, relationships, and mental health over dark, atmospheric production.
  • B. FL
    FL is the standard two-letter United States Postal Service abbreviation for the state of Florida.
  • C. FL
    FL is the international vehicle registration code for the Principality of Liechtenstein.
  • D. FC
    FC is the standard abbreviation for Fibre Channel, a high-speed network technology primarily used to connect computer data storage in storage area networks.
  • E. FC
    FC is the vehicle registration and administrative code used to identify the Italian province of Forlì-Cesena.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2303c6881909405f0d6089dbe12 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712be7f9c8190b2667fc4c8d5f601 completed March 27, 2026, 11:29 p.m.
NEDg Description generation batch_69c713842b9c8190ae31eba0bd449968 completed March 27, 2026, 11:32 p.m.
NED2 Entity disambiguation (via description) batch_69c71444e9ec8190a68531ed29fd9377 completed March 27, 2026, 11:35 p.m.
Created at: March 27, 2026, 2:12 p.m.