Triple

T5301176
Position Surface form Disambiguated ID Type / Status
Subject Ortenaukreis E119983 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object WOL
WOL is a German vehicle registration code formerly used for the town of Wolfach in the Ortenaukreis district of Baden-Württemberg.
 E509541 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: WOL | Statement: [Ortenaukreis, vehicleRegistrationCode, WOL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: WOL
Context triple: [Ortenaukreis, vehicleRegistrationCode, WOL]
  • A. wol
    "wol" is the ISO 639-3 language code for Wolof, a major Atlantic language spoken primarily in Senegal, The Gambia, and Mauritania.
  • B. WOFL
    WOFL is a Fox-affiliated television station serving the Orlando, Florida media market.
  • C. WoS
    WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
  • D. WOR
    WOR is a historic New York City AM radio station known for its long-running news, talk, and entertainment programming.
  • E. Wo!!
    Wo!! is a hit Nigerian street-hop single by rapper Olamide, known for its catchy beat, dance-inducing vibe, and massive popularity across Nigeria.
  • 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: WOL
Triple: [Ortenaukreis, vehicleRegistrationCode, WOL]
Generated description
WOL is a German vehicle registration code formerly used for the town of Wolfach in the Ortenaukreis district of Baden-Württemberg.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: WOL
Target entity description: WOL is a German vehicle registration code formerly used for the town of Wolfach in the Ortenaukreis district of Baden-Württemberg.
  • A. wol
    "wol" is the ISO 639-3 language code for Wolof, a major Atlantic language spoken primarily in Senegal, The Gambia, and Mauritania.
  • B. WOFL
    WOFL is a Fox-affiliated television station serving the Orlando, Florida media market.
  • C. WoS
    WoS is a racing-themed video game centered on high-speed car competitions and online multiplayer gameplay.
  • D. WOR
    WOR is a historic New York City AM radio station known for its long-running news, talk, and entertainment programming.
  • E. Wo!!
    Wo!! is a hit Nigerian street-hop single by rapper Olamide, known for its catchy beat, dance-inducing vibe, and massive popularity across Nigeria.
  • 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_69bd44704be88190acdb2ac481b0ff55 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8509f67c8190b2f82a8370301a59 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10f040f48190b34a586d362264ee completed March 21, 2026, 9:43 p.m.
NEDg Description generation batch_69bf11635b9c819092130c46caea9306 completed March 21, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_69bf11e982d08190bc74312bf6ee7127 completed March 21, 2026, 9:47 p.m.
Created at: March 20, 2026, 1:53 p.m.