Triple

T3649453
Position Surface form Disambiguated ID Type / Status
Subject London Paddington E77382 entity
Predicate hasIataCode P2569 FINISHED
Object QQP
QQP is the National Rail station code used to identify London Paddington railway station in the United Kingdom.
 E376478 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: QQP | Statement: [London Paddington, hasIataCode, QQP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: QQP
Context triple: [London Paddington, hasIataCode, QQP]
  • A. QQQ
    QQQ is a popular exchange-traded fund (ETF) that tracks the performance of the Nasdaq-100 Index, providing exposure to many of the largest non-financial companies listed on the Nasdaq stock market.
  • B. WeChat
    WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
  • C. QQS
    QQS is the IATA station code for London St Pancras International, a major central London railway terminus and international high-speed rail hub.
  • D. QQS
    QQS is the IATA airport code for the Shuttle Landing Facility at NASA’s Kennedy Space Center in Florida, historically used for Space Shuttle landings.
  • E. Cốc Cốc
    Cốc Cốc is a Vietnamese web browser and search engine tailored to local users, offering features like improved downloading, integrated ad-blocking, and support for Vietnamese language and services.
  • 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: QQP
Triple: [London Paddington, hasIataCode, QQP]
Generated description
QQP is the National Rail station code used to identify London Paddington railway station in the United Kingdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: QQP
Target entity description: QQP is the National Rail station code used to identify London Paddington railway station in the United Kingdom.
  • A. QQQ
    QQQ is a popular exchange-traded fund (ETF) that tracks the performance of the Nasdaq-100 Index, providing exposure to many of the largest non-financial companies listed on the Nasdaq stock market.
  • B. WeChat
    WeChat is a Chinese multi-purpose mobile app developed by Tencent that combines messaging, social media, and payment services into a single platform.
  • C. QQS
    QQS is the IATA station code for London St Pancras International, a major central London railway terminus and international high-speed rail hub.
  • D. QQS
    QQS is the IATA airport code for the Shuttle Landing Facility at NASA’s Kennedy Space Center in Florida, historically used for Space Shuttle landings.
  • E. Cốc Cốc
    Cốc Cốc is a Vietnamese web browser and search engine tailored to local users, offering features like improved downloading, integrated ad-blocking, and support for Vietnamese language and services.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc38fa1988190b630329700afc3dd completed March 8, 2026, 6:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f3c85348190b1d16179294f7f09 completed March 13, 2026, 5:54 p.m.
NEDg Description generation batch_69b4520fb96481909f54af01fc4a3bbe completed March 13, 2026, 6:06 p.m.
NED2 Entity disambiguation (via description) batch_69b45df65f5c8190a9f25e7da926222a completed March 13, 2026, 6:56 p.m.
Created at: March 8, 2026, 3:24 p.m.