Triple

T3033736
Position Surface form Disambiguated ID Type / Status
Subject Lillehammer railway station E82956 entity
Predicate hasStationCode P1289 FINISHED
Object LHM
LHM is the station code for Lillehammer railway station in Norway.
 E321488 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: LHM | Statement: [Lillehammer railway station, hasStationCode, LHM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LHM
Context triple: [Lillehammer railway station, hasStationCode, LHM]
  • A. LH
    LH is the two-letter IATA airline designator used to identify Lufthansa flights in global aviation systems.
  • B. 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.
  • C. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • D. HMA
    HMA is a European network of national medicines regulatory authorities that collaborates to ensure the quality, safety, and efficacy of medicinal products across member states.
  • E. LMT
    LMT is the stock ticker symbol for Lockheed Martin Corporation, a major American aerospace, defense, and security company.
  • 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: LHM
Triple: [Lillehammer railway station, hasStationCode, LHM]
Generated description
LHM is the station code for Lillehammer railway station in Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LHM
Target entity description: LHM is the station code for Lillehammer railway station in Norway.
  • A. LH
    LH is the two-letter IATA airline designator used to identify Lufthansa flights in global aviation systems.
  • B. 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.
  • C. Lm
    Lm is the currency symbol that was used to denote the Maltese lira, Malta’s former national currency before adoption of the euro.
  • D. HMA
    HMA is a European network of national medicines regulatory authorities that collaborates to ensure the quality, safety, and efficacy of medicinal products across member states.
  • E. LMT
    LMT is the stock ticker symbol for Lockheed Martin Corporation, a major American aerospace, defense, and security company.
  • 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_69ad8b21a62881908ec5dd4fba4a187c completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9af13ce48190bda4f5ca0ffe6285 completed March 8, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1dec30d8081909d6ee691e5e51434 completed March 11, 2026, 9:29 p.m.
NEDg Description generation batch_69b1e297ddc0819092942cdf8a4f9440 completed March 11, 2026, 9:46 p.m.
NED2 Entity disambiguation (via description) batch_69b1e2f519108190883ee481b763b67f completed March 11, 2026, 9:47 p.m.
Created at: March 8, 2026, 3:01 p.m.