Triple

T7811158
Position Surface form Disambiguated ID Type / Status
Subject Langho railway station E180686 entity
Predicate hasStationCode P1289 FINISHED
Object LHO
LHO is the National Rail station code for Langho railway station in Lancashire, England.
E694615 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: LHO | Statement: [Langho railway station, hasStationCode, LHO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: LHO
Context triple: [Langho railway station, hasStationCode, LHO]
  • A. LHD
    LHD is the National Rail station code for Leatherhead railway station in Surrey, England.
  • B. LH
    LH is the two-letter IATA airline designator used to identify Lufthansa flights in global aviation systems.
  • C. LH
    The LH is a mid-1970s generation of the Holden Torana, an Australian compact car series known for its performance-oriented variants and motorsport success.
  • D. LHM
    LHM is the station code for Lillehammer railway station in Norway.
  • E. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • 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: LHO
Triple: [Langho railway station, hasStationCode, LHO]
Generated description
LHO is the National Rail station code for Langho railway station in Lancashire, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: LHO
Target entity description: LHO is the National Rail station code for Langho railway station in Lancashire, England.
  • A. LHD
    LHD is the National Rail station code for Leatherhead railway station in Surrey, England.
  • B. LH
    LH is the two-letter IATA airline designator used to identify Lufthansa flights in global aviation systems.
  • C. LH
    The LH is a mid-1970s generation of the Holden Torana, an Australian compact car series known for its performance-oriented variants and motorsport success.
  • D. LHM
    LHM is the station code for Lillehammer railway station in Norway.
  • E. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • 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_69ca827f6f148190beca4e245b993506 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69caf78cd1cc8190b4cdd9850e1e2bb7 completed March 30, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb14651d488190b1bf6b875a2ebccd completed March 31, 2026, 12:25 a.m.
NEDg Description generation batch_69cb173190a88190b31fd7973bc19d43 completed March 31, 2026, 12:37 a.m.
NED2 Entity disambiguation (via description) batch_69cb1a56d25881908b8413b82edf5508 completed March 31, 2026, 12:50 a.m.
Created at: March 30, 2026, 4:37 p.m.