Triple

T8787885
Position Surface form Disambiguated ID Type / Status
Subject Traunstein district E209087 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object LF
LF is a German vehicle registration code assigned to the Traunstein district in the state of Bavaria.
 E756953 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: LF | Statement: [Traunstein district, hasVehicleRegistrationCode, LF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LF
Context triple: [Traunstein district, hasVehicleRegistrationCode, LF]
  • A. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • B. FL
    FL is the standard two-letter United States Postal Service abbreviation for the state of Florida.
  • C. FL
    FL is the international vehicle registration code for the Principality of Liechtenstein.
  • D. FL
    FL is the vehicle registration code used on license plates for the German city of Flensburg.
  • E. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • 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: LF
Triple: [Traunstein district, hasVehicleRegistrationCode, LF]
Generated description
LF is a German vehicle registration code assigned to the Traunstein district in the state of Bavaria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LF
Target entity description: LF is a German vehicle registration code assigned to the Traunstein district in the state of Bavaria.
  • A. LF
    LF is the commonly used abbreviation for the Linux Foundation, a nonprofit organization that supports and promotes the development of the Linux kernel and other open-source software projects.
  • B. FL
    FL is the standard two-letter United States Postal Service abbreviation for the state of Florida.
  • C. FL
    FL is the international vehicle registration code for the Principality of Liechtenstein.
  • D. FL
    FL is the vehicle registration code used on license plates for the German city of Flensburg.
  • E. LD
    LD is the IATA airline designator assigned to Air Hong Kong, a cargo airline based in Hong Kong.
  • 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_69ca836168108190bb43d3dc235c1f55 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5f89a84c819085d4cfe4e6dfbda8 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf520678f48190a0af3df75df9b269 completed April 3, 2026, 5:37 a.m.
NEDg Description generation batch_69cf5490df348190a31f300f0f4dae71 completed April 3, 2026, 5:48 a.m.
NED2 Entity disambiguation (via description) batch_69cf5565bc108190a283772608fd28de completed April 3, 2026, 5:51 a.m.
Created at: March 30, 2026, 6:43 p.m.