Triple

T11267011
Position Surface form Disambiguated ID Type / Status
Subject Ligovsky Prospekt metro station E266711 entity
Predicate hasStationCode P1289 FINISHED
Object ЛП
ЛП is the station code used to designate Ligovsky Prospekt, a station of the Saint Petersburg Metro in Russia.
 E915073 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: ЛП | Statement: [Ligovsky Prospekt metro station, hasStationCode, ЛП]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ЛП
Context triple: [Ligovsky Prospekt metro station, hasStationCode, ЛП]
  • A. l_P
    l_P is the standard symbol denoting the Planck length, the fundamental quantum scale of length in theoretical physics.
  • B. PLP
    PLP is a political party known as the Parti de la Liberté et du Progrès, typically associated with liberal and progressive policies.
  • C. PLP
    PLP is the commonly used abbreviation for the Parliamentary Labour Party, the grouping of Labour Members of Parliament in the UK House of Commons.
  • D. LPP
    LPP is the IATA airport code for Lappeenranta Airport in Lappeenranta, Finland.
  • E. LAP
    LAP is the ICAO airline designator used to identify LATAM Airlines Paraguay in international aviation operations.
  • 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: ЛП
Triple: [Ligovsky Prospekt metro station, hasStationCode, ЛП]
Generated description
ЛП is the station code used to designate Ligovsky Prospekt, a station of the Saint Petersburg Metro in Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ЛП
Target entity description: ЛП is the station code used to designate Ligovsky Prospekt, a station of the Saint Petersburg Metro in Russia.
  • A. l_P
    l_P is the standard symbol denoting the Planck length, the fundamental quantum scale of length in theoretical physics.
  • B. PLP
    PLP is a political party known as the Parti de la Liberté et du Progrès, typically associated with liberal and progressive policies.
  • C. PLP
    PLP is the commonly used abbreviation for the Parliamentary Labour Party, the grouping of Labour Members of Parliament in the UK House of Commons.
  • D. LPP
    LPP is the IATA airport code for Lappeenranta Airport in Lappeenranta, Finland.
  • E. LAP
    LAP is the ICAO airline designator used to identify LATAM Airlines Paraguay in international aviation operations.
  • 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_69d6aac8c2f48190ad0596f1f89f0470 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e94e5e3c8190a31995d55d20d7ed completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4ccd52c20819093e03bba2fd359b7 completed April 19, 2026, 12:38 p.m.
NEDg Description generation batch_69e4d9ed6a048190ae7476d44cee6a6e completed April 19, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_69e4ddb1b4c8819087699bc73610c7f8 completed April 19, 2026, 1:50 p.m.
Created at: April 8, 2026, 9:31 p.m.