Triple

T15424028
Position Surface form Disambiguated ID Type / Status
Subject Knightsbridge tube station E369456 entity
Predicate stationCode P1289 FINISHED
Object KNI
KNI is the three-letter station code used to identify Knightsbridge tube station on the London Underground network.
E1155825 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: KNI | Statement: [Knightsbridge tube station, stationCode, KNI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KNI
Context triple: [Knightsbridge tube station, stationCode, KNI]
  • A. KNA
    KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
  • B. KNA
    KNA is the ICAO airline designator assigned to Kunming Airlines, a Chinese carrier based in Kunming, Yunnan.
  • C. KNO
    KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
  • D. KWI
    KWI is the three-letter IATA airport code for Kuwait International Airport, the main international gateway to Kuwait.
  • E. KNS
    KNS is the Polish vehicle registration code assigned to the Nowy Sącz area in the Lesser Poland Voivodeship.
  • 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: KNI
Triple: [Knightsbridge tube station, stationCode, KNI]
Generated description
KNI is the three-letter station code used to identify Knightsbridge tube station on the London Underground network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: KNI
Target entity description: KNI is the three-letter station code used to identify Knightsbridge tube station on the London Underground network.
  • A. KNA
    KNA is the ICAO airline designator assigned to Kunming Airlines, a Chinese carrier based in Kunming, Yunnan.
  • B. KNA
    KNA is the three-letter ISO 3166-1 alpha-3 country code assigned to Saint Kitts and Nevis.
  • C. KNO
    KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
  • D. KWI
    KWI is the three-letter IATA airport code for Kuwait International Airport, the main international gateway to Kuwait.
  • E. KNS
    KNS is the Polish vehicle registration code assigned to the Nowy Sącz area in the Lesser Poland Voivodeship.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec032548190840b558dde6057c7 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a7ed0ec8190b8086f78df965b61 completed May 9, 2026, 11:29 a.m.
NEDg Description generation batch_69ff1b3c563481908418411a977df343 completed May 9, 2026, 11:32 a.m.
NED2 Entity disambiguation (via description) batch_69ff1c0ad5448190903dc38f78512f3b completed May 9, 2026, 11:35 a.m.
Created at: April 10, 2026, 3:20 a.m.