Triple

T4953383
Position Surface form Disambiguated ID Type / Status
Subject Regierungsbezirk Stuttgart E111220 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object ES
ES is the vehicle registration code for the district of Esslingen in the Stuttgart region of Baden-Württemberg, Germany.
 E483341 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: ES | Statement: [Regierungsbezirk Stuttgart, hasVehicleRegistrationCode, ES]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ES
Context triple: [Regierungsbezirk Stuttgart, hasVehicleRegistrationCode, ES]
  • A. ES
    ES is the commonly used abbreviation for European Solidarity, a Polish political party.
  • B. ES
    ES is the ticker symbol for the E-mini S&P 500 futures contract, a widely traded equity index derivative on the Chicago Mercantile Exchange used for hedging and speculating on the S&P 500.
  • C. ES
    ES is the ISO 3166-1 alpha-2 country code for Spain, a European nation on the Iberian Peninsula.
  • D. ESP
    ESP is the three-letter FIFA country code used to represent the Spain national football team in international competitions and official records.
  • E. ESP
    ESP (extrasensory perception) is the purported ability to gain information through means beyond the known physical senses, such as telepathy, clairvoyance, or precognition.
  • 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: ES
Triple: [Regierungsbezirk Stuttgart, hasVehicleRegistrationCode, ES]
Generated description
ES is the vehicle registration code for the district of Esslingen in the Stuttgart region of Baden-Württemberg, Germany.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ES
Target entity description: ES is the vehicle registration code for the district of Esslingen in the Stuttgart region of Baden-Württemberg, Germany.
  • A. ES
    ES is the ticker symbol for the E-mini S&P 500 futures contract, a widely traded equity index derivative on the Chicago Mercantile Exchange used for hedging and speculating on the S&P 500.
  • B. ES
    ES is the commonly used abbreviation for European Solidarity, a Polish political party.
  • C. ES
    ES is the ISO 3166-1 alpha-2 country code for Spain, a European nation on the Iberian Peninsula.
  • D. ESP
    ESP is the three-letter FIFA country code used to represent the Spain national football team in international competitions and official records.
  • E. ESP
    ESP (extrasensory perception) is the purported ability to gain information through means beyond the known physical senses, such as telepathy, clairvoyance, or precognition.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71b82dd88190adfb08c3b3191fe0 completed March 20, 2026, 4:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81d773bc8190861be7ad83de6c2a completed March 21, 2026, 11:32 a.m.
NEDg Description generation batch_69be82dcc280819098eac824370b1af0 completed March 21, 2026, 11:37 a.m.
NED2 Entity disambiguation (via description) batch_69be8349507481908643591de7f03f42 completed March 21, 2026, 11:38 a.m.
Created at: March 20, 2026, 1:31 p.m.