Triple

T9523191
Position Surface form Disambiguated ID Type / Status
Subject Province of Caserta E229694 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object CE
CE is the Italian vehicle registration code assigned to the Province of Caserta in the Campania region.
 E803998 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: CE | Statement: [Province of Caserta, vehicleRegistrationCode, CE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: CE
Context triple: [Province of Caserta, vehicleRegistrationCode, CE]
  • A. CE
    CE is the vehicle registration code used on license plates for the Spanish autonomous city of Ceuta in North Africa.
  • B. CE
    CE is the vehicle registration code used for the district of Celle in Lower Saxony, Germany.
  • C. CE
    CE is the standard abbreviation for the Catholic Encyclopedia, a comprehensive reference work on Catholic doctrine, history, and practice.
  • D. CE
    CE is the stock ticker symbol for Celanese Corporation, a global chemical and specialty materials company traded on the New York Stock Exchange.
  • E. EC
    EC is the two-letter ISO 3166-1 alpha-2 country code assigned to Ecuador.
  • 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: CE
Triple: [Province of Caserta, vehicleRegistrationCode, CE]
Generated description
CE is the Italian vehicle registration code assigned to the Province of Caserta in the Campania region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: CE
Target entity description: CE is the Italian vehicle registration code assigned to the Province of Caserta in the Campania region.
  • A. CE
    CE is the vehicle registration code used on license plates for the Spanish autonomous city of Ceuta in North Africa.
  • B. CE
    CE is the vehicle registration code used for the district of Celle in Lower Saxony, Germany.
  • C. CE
    CE is the standard abbreviation for the Catholic Encyclopedia, a comprehensive reference work on Catholic doctrine, history, and practice.
  • D. CE
    CE is the stock ticker symbol for Celanese Corporation, a global chemical and specialty materials company traded on the New York Stock Exchange.
  • E. EC
    EC is the commonly used abbreviation for the Election Commission of Bangladesh, the constitutional body responsible for overseeing and conducting elections in the country.
  • 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_69ca847870a881909d8d751a7d29da39 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9898e0b48190a3e3f0f1616d5055 completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a61fbd08190bb68ffe29da3a34a completed April 4, 2026, 4:20 p.m.
NEDg Description generation batch_69d13c0344388190aefc18936b17b9f0 completed April 4, 2026, 4:27 p.m.
NED2 Entity disambiguation (via description) batch_69d13c7b2954819096a276e083d4fed1 completed April 4, 2026, 4:29 p.m.
Created at: March 30, 2026, 7:59 p.m.