Triple

T738794
Position Surface form Disambiguated ID Type / Status
Subject Chihuahua E14995 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object CHH
CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
 E87799 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: CHH | Statement: [Chihuahua, vehicleRegistrationCode, CHH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CHH
Context triple: [Chihuahua, vehicleRegistrationCode, CHH]
  • A. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • B. BCCh
    BCCh is the acronym for the Central Bank of Chile, the country’s autonomous monetary authority responsible for maintaining price stability and financial system soundness.
  • C. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • D. TCH
    TCH was the International Ice Hockey Federation (IIHF) country code used to represent the Czechoslovakia men's national ice hockey team in international competition.
  • E. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • 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: CHH
Triple: [Chihuahua, vehicleRegistrationCode, CHH]
Generated description
CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CHH
Target entity description: CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
  • A. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • B. BCCh
    BCCh is the acronym for the Central Bank of Chile, the country’s autonomous monetary authority responsible for maintaining price stability and financial system soundness.
  • C. LCH
    LCH is a leading global clearing house that provides central counterparty clearing services for a wide range of financial markets and asset classes.
  • D. TCH
    TCH was the International Ice Hockey Federation (IIHF) country code used to represent the Czechoslovakia men's national ice hockey team in international competition.
  • E. HAA
    HAA is the Harvard Alumni Association, the organization that connects and serves Harvard University’s global community of alumni.
  • 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_69a4934d9930819099eed80096b0597d completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a5f1c9888190b2817138c6893cfe completed March 1, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a618c248190ab1bcecba04d3da8 completed March 3, 2026, 2:41 a.m.
NEDg Description generation batch_69a64b4c8bb88190aa413a4bed256129 completed March 3, 2026, 2:45 a.m.
NED2 Entity disambiguation (via description) batch_69a64beaafa0819099b02cca0f6c79b7 completed March 3, 2026, 2:48 a.m.
Created at: March 1, 2026, 7:37 p.m.