Triple

T15094781
Position Surface form Disambiguated ID Type / Status
Subject Panipat Junction E360510 entity
Predicate railwayStationCode P1289 FINISHED
Object PNP
PNP is the station code for Panipat Junction, a major railway hub in the Indian state of Haryana.
 E1137556 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: PNP | Statement: [Panipat Junction, railwayStationCode, PNP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: PNP
Context triple: [Panipat Junction, railwayStationCode, PNP]
  • A. PNP
    PNP is the national police force of the Philippines responsible for law enforcement, crime prevention, and public safety across the country.
  • B. PNP
    The PNP is the national law enforcement agency of Peru responsible for maintaining public order, preventing and investigating crime, and ensuring internal security across the country.
  • C. PNP
    PNP is a major social-democratic political party in Jamaica known formally as the People's National Party.
  • D. PN
    PN is the station code for Penn–North station on the Baltimore Metro SubwayLink system.
  • E. PN
    PN is the vehicle registration code used for the Italian city and province of Pordenone in the Friuli Venezia Giulia region.
  • 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: PNP
Triple: [Panipat Junction, railwayStationCode, PNP]
Generated description
PNP is the station code for Panipat Junction, a major railway hub in the Indian state of Haryana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: PNP
Target entity description: PNP is the station code for Panipat Junction, a major railway hub in the Indian state of Haryana.
  • A. PNP
    The PNP is the national law enforcement agency of Peru responsible for maintaining public order, preventing and investigating crime, and ensuring internal security across the country.
  • B. PNP
    PNP is the national police force of the Philippines responsible for law enforcement, crime prevention, and public safety across the country.
  • C. PNP
    PNP is a major social-democratic political party in Jamaica known formally as the People's National Party.
  • D. PN
    PN is the official abbreviation for the Philippine Navy, the naval warfare branch of the Armed Forces of the Philippines.
  • E. PN
    PN is the station code for Penn–North station on the Baltimore Metro SubwayLink system.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0054571a48190a57055c0d6e90f82 completed April 15, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69feae21134c81908939ad6ce46703d8 completed May 9, 2026, 3:46 a.m.
NEDg Description generation batch_69feb37427a881908cf95f60b06251d4 completed May 9, 2026, 4:09 a.m.
NED2 Entity disambiguation (via description) batch_69feb429517c8190a91cc6b50345d889 completed May 9, 2026, 4:12 a.m.
Created at: April 10, 2026, 3:04 a.m.