Triple

T17277671
Position Surface form Disambiguated ID Type / Status
Subject Queen Victoria E419433 entity
Predicate callSign P1565 FINISHED
Object ZCEF9
ZCEF9 is a callsign designation historically associated with Queen Victoria, likely used as an identifying code in communication or transportation records.
 E1260625 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: ZCEF9 | Statement: [Queen Victoria, callSign, ZCEF9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZCEF9
Context triple: [Queen Victoria, callSign, ZCEF9]
  • A. Zefiro 9
    Zefiro 9 is a solid-propellant upper-stage rocket motor used as the third stage of the European Vega small-lift launch vehicle.
  • B. ZKF
    ZKF is the station code used to identify King’s Cross St Pancras Underground station on the London Underground network.
  • C. ZSFZ
    ZSFZ is the ICAO airport code for Fuzhou Changle International Airport, the main international airport serving Fuzhou in Fujian Province, China.
  • D. ZFA
    ZFA is a variant of set theory that allows sets with atoms (urelements), often used in constructing permutation models like those of Fraenkel–Mostowski.
  • E. CIEF
    CIEF is the abbreviated name for the Canton Fair, China’s largest and oldest comprehensive trade exhibition held biannually in Guangzhou.
  • 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: ZCEF9
Triple: [Queen Victoria, callSign, ZCEF9]
Generated description
ZCEF9 is a callsign designation historically associated with Queen Victoria, likely used as an identifying code in communication or transportation records.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZCEF9
Target entity description: ZCEF9 is a callsign designation historically associated with Queen Victoria, likely used as an identifying code in communication or transportation records.
  • A. Zefiro 9
    Zefiro 9 is a solid-propellant upper-stage rocket motor used as the third stage of the European Vega small-lift launch vehicle.
  • B. ZKF
    ZKF is the station code used to identify King’s Cross St Pancras Underground station on the London Underground network.
  • C. ZSFZ
    ZSFZ is the ICAO airport code for Fuzhou Changle International Airport, the main international airport serving Fuzhou in Fujian Province, China.
  • D. ZFA
    ZFA is a variant of set theory that allows sets with atoms (urelements), often used in constructing permutation models like those of Fraenkel–Mostowski.
  • E. CIEF
    CIEF is the abbreviated name for the Canton Fair, China’s largest and oldest comprehensive trade exhibition held biannually in Guangzhou.
  • 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_69d886da626481908a14ce7830329a35 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e43326ec908190934a858c30cca880 completed April 19, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0179513ffc81908bac515823e88a1a completed May 11, 2026, 6:38 a.m.
NEDg Description generation batch_6a017c351e908190bcd7bb751dc7f949 completed May 11, 2026, 6:50 a.m.
NED2 Entity disambiguation (via description) batch_6a017cad99688190aeaa388bf2d7d603 completed May 11, 2026, 6:52 a.m.
Created at: April 10, 2026, 5:40 a.m.