Triple

T19016339
Position Surface form Disambiguated ID Type / Status
Subject Udhampur railway station E465358 entity
Predicate hasStationCode P1289 FINISHED
Object UHP
UHP is the Indian Railways station code assigned to Udhampur railway station in Jammu and Kashmir, India.
 E1354481 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: UHP | Statement: [Udhampur railway station, hasStationCode, UHP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: UHP
Context triple: [Udhampur railway station, hasStationCode, UHP]
  • A. UHPP
    UHPP is the ICAO airport code for Petropavlovsk-Kamchatsky Airport, a major air gateway on Russia’s Kamchatka Peninsula.
  • B. UHS
    UHS is the stock ticker symbol for Universal Health Services, a major U.S.-based hospital and healthcare services company.
  • C. UPE
    UPE is the abbreviation for Université Paris-Est, a French higher education and research institution located in the eastern part of the Paris metropolitan area.
  • D. UPT
    UPT is the National Rail station code for Upton railway station in Merseyside, England.
  • E. UHF
    UHF is a 1989 cult comedy film starring "Weird Al" Yankovic as a daydreaming misfit who turns a failing UHF television station into a bizarre hit.
  • 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: UHP
Triple: [Udhampur railway station, hasStationCode, UHP]
Generated description
UHP is the Indian Railways station code assigned to Udhampur railway station in Jammu and Kashmir, India.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: UHP
Target entity description: UHP is the Indian Railways station code assigned to Udhampur railway station in Jammu and Kashmir, India.
  • A. UHPP
    UHPP is the ICAO airport code for Petropavlovsk-Kamchatsky Airport, a major air gateway on Russia’s Kamchatka Peninsula.
  • B. UHS
    UHS is the stock ticker symbol for Universal Health Services, a major U.S.-based hospital and healthcare services company.
  • C. UPE
    UPE is the abbreviation for Université Paris-Est, a French higher education and research institution located in the eastern part of the Paris metropolitan area.
  • D. UPT
    UPT is the National Rail station code for Upton railway station in Merseyside, England.
  • E. UHF
    UHF is a 1989 cult comedy film starring "Weird Al" Yankovic as a daydreaming misfit who turns a failing UHF television station into a bizarre hit.
  • 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_69d8dd025c188190a1d81f5b4ec7e2c6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6db04fc819094709f223e30a526 completed April 20, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05be504c248190ac0aeea678ea5c67 completed May 14, 2026, 12:21 p.m.
NEDg Description generation batch_6a05bf8691f08190baa0e97f588973cb completed May 14, 2026, 12:26 p.m.
NED2 Entity disambiguation (via description) batch_6a05bff32d088190b60ecf78f97848b9 completed May 14, 2026, 12:28 p.m.
Created at: April 10, 2026, 12:02 p.m.