Triple

T559111
Position Surface form Disambiguated ID Type / Status
Subject Zurich E13407 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object ZH
ZH is the official vehicle registration code used for the Swiss canton of Zurich.
 E70162 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: ZH | Statement: [Zurich, vehicleRegistrationCode, ZH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZH
Context triple: [Zurich, vehicleRegistrationCode, ZH]
  • A. Z
    Z is the neutral elementary particle known as the Z boson, a carrier of the weak nuclear force in the Standard Model of particle physics.
  • B. ZZ
    ZZ is an aircraft registration prefix used to identify certain aircraft, such as those in the Voyager KC2 fleet.
  • C. ZWN
    ZWN is a former currency code used to denote an early version of the Zimbabwean dollar in international financial and foreign exchange contexts.
  • D. ZM
    ZM is the stock ticker symbol for Zoom Video Communications, a leading provider of cloud-based video conferencing and online collaboration services.
  • E. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • 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: ZH
Triple: [Zurich, vehicleRegistrationCode, ZH]
Generated description
ZH is the official vehicle registration code used for the Swiss canton of Zurich.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZH
Target entity description: ZH is the official vehicle registration code used for the Swiss canton of Zurich.
  • A. Z
    Z is the neutral elementary particle known as the Z boson, a carrier of the weak nuclear force in the Standard Model of particle physics.
  • B. ZZ
    ZZ is an aircraft registration prefix used to identify certain aircraft, such as those in the Voyager KC2 fleet.
  • C. ZWN
    ZWN is a former currency code used to denote an early version of the Zimbabwean dollar in international financial and foreign exchange contexts.
  • D. ZM
    ZM is the stock ticker symbol for Zoom Video Communications, a leading provider of cloud-based video conferencing and online collaboration services.
  • E. ZUEL
    ZUEL is a prominent Chinese university specializing in economics, law, and related social sciences, located in Wuhan, Hubei Province.
  • 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_69a4933edcf08190b35ecfd6014caee6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a499df43f08190b514a38d36fc271d completed March 1, 2026, 7:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e9bb3b28819099ed0027d948483a completed March 2, 2026, 1:36 a.m.
NEDg Description generation batch_69a4eab98cf08190a0923f42e42667ed completed March 2, 2026, 1:41 a.m.
NED2 Entity disambiguation (via description) batch_69a4eb14d6d88190885d6eac9dfc3db8 completed March 2, 2026, 1:42 a.m.
Created at: March 1, 2026, 7:32 p.m.