Triple

T4591766
Position Surface form Disambiguated ID Type / Status
Subject Jenkintown–Wyncote station E103505 entity
Predicate code P1537 FINISHED
Object JEK
JEK is the station code for Jenkintown–Wyncote, a major SEPTA Regional Rail hub in the northern suburbs of Philadelphia.
 E454778 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: JEK | Statement: [Jenkintown–Wyncote station, code, JEK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: JEK
Context triple: [Jenkintown–Wyncote station, code, JEK]
  • A. Jep
    Jep is a masculine given name, often used as a short form or variant of names like Jepsen or Jeppe in Scandinavian contexts.
  • B. Jak
    Jak is the main protagonist of the Jak and Daxter video game series, a heroic adventurer who battles oppressive regimes and dark forces across multiple worlds.
  • C. JOK
    JOK is the standard abbreviation used for Jokerit, a professional ice hockey club based in Helsinki, Finland.
  • D. KJK
    KJK is the IATA airport code for Koksijde Air Base in Belgium.
  • E. Jebe
    Jebe was one of Genghis Khan’s most brilliant generals, renowned for his daring cavalry campaigns and key role in the early Mongol conquests across Central Asia and into Eastern Europe.
  • 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: JEK
Triple: [Jenkintown–Wyncote station, code, JEK]
Generated description
JEK is the station code for Jenkintown–Wyncote, a major SEPTA Regional Rail hub in the northern suburbs of Philadelphia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: JEK
Target entity description: JEK is the station code for Jenkintown–Wyncote, a major SEPTA Regional Rail hub in the northern suburbs of Philadelphia.
  • A. Jep
    Jep is a masculine given name, often used as a short form or variant of names like Jepsen or Jeppe in Scandinavian contexts.
  • B. Jak
    Jak is the main protagonist of the Jak and Daxter video game series, a heroic adventurer who battles oppressive regimes and dark forces across multiple worlds.
  • C. JOK
    JOK is the standard abbreviation used for Jokerit, a professional ice hockey club based in Helsinki, Finland.
  • D. KJK
    KJK is the IATA airport code for Koksijde Air Base in Belgium.
  • E. Jebe
    Jebe was one of Genghis Khan’s most brilliant generals, renowned for his daring cavalry campaigns and key role in the early Mongol conquests across Central Asia and into Eastern Europe.
  • 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_69bd43dccaf08190aa89e9991a289719 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd592520ec8190b1bd4cb4d9b94c94 completed March 20, 2026, 2:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0cdc7e8819088758c1d6d8e866d completed March 21, 2026, 12:05 a.m.
NEDg Description generation batch_69bde21999688190afc48da7fa2cd869 completed March 21, 2026, 12:11 a.m.
NED2 Entity disambiguation (via description) batch_69bde283e1988190bfa3545d2a362294 completed March 21, 2026, 12:12 a.m.
Created at: March 20, 2026, 1:11 p.m.