Triple

T7768066
Position Surface form Disambiguated ID Type / Status
Subject King’s Cross St Pancras Underground station E178999 entity
Predicate hasStationCode P1289 FINISHED
Object ZKF
ZKF is the station code used to identify King’s Cross St Pancras Underground station on the London Underground network.
 E687281 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: ZKF | Statement: [King’s Cross St Pancras Underground station, hasStationCode, ZKF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZKF
Context triple: [King’s Cross St Pancras Underground station, hasStationCode, ZKF]
  • A. GFKZ
    GFKZ is the radio call sign assigned to the British Royal Research Ship (RRS) Charles Darwin, an oceanographic research vessel.
  • B. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • C. KZT
    KZT is the currency code for the Kazakhstani tenge, the official monetary unit of Kazakhstan.
  • D. ZSFZ
    ZSFZ is the ICAO airport code for Fuzhou Changle International Airport, the main international airport serving Fuzhou in Fujian Province, China.
  • E. ZF
    ZF is the standard axiomatic framework for set theory that underpins much of modern mathematics.
  • 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: ZKF
Triple: [King’s Cross St Pancras Underground station, hasStationCode, ZKF]
Generated description
ZKF is the station code used to identify King’s Cross St Pancras Underground station on the London Underground network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZKF
Target entity description: ZKF is the station code used to identify King’s Cross St Pancras Underground station on the London Underground network.
  • A. GFKZ
    GFKZ is the radio call sign assigned to the British Royal Research Ship (RRS) Charles Darwin, an oceanographic research vessel.
  • B. KZ
    KZ is the two-letter ISO 3166-1 alpha-2 country code assigned to Kazakhstan for international standardization and identification.
  • C. KZT
    KZT is the currency code for the Kazakhstani tenge, the official monetary unit of Kazakhstan.
  • D. ZSFZ
    ZSFZ is the ICAO airport code for Fuzhou Changle International Airport, the main international airport serving Fuzhou in Fujian Province, China.
  • E. ZF
    ZF is the standard axiomatic framework for set theory that underpins much of modern mathematics.
  • 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_69c69f30602c819082ab52cd4af5c592 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c70435b7f88190a5e68e6ae701c58f completed March 27, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8c7e4976c81909ff34dcdcae96999 completed March 29, 2026, 6:34 a.m.
NEDg Description generation batch_69c8c8b75b848190a67de2040d563f86 completed March 29, 2026, 6:37 a.m.
NED2 Entity disambiguation (via description) batch_69c8c941814081909d299df5cd714c71 completed March 29, 2026, 6:40 a.m.
Created at: March 27, 2026, 4:11 p.m.