Triple

T8708712
Position Surface form Disambiguated ID Type / Status
Subject Ostrowiec Świętokrzyski E206717 entity
Predicate carPlatesCode P1173 FINISHED
Object TOS
TOS is the vehicle registration code used on license plates for cars registered in Ostrowiec Świętokrzyski, Poland.
 E200571 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: TOS | Statement: [Ostrowiec Świętokrzyski, carPlatesCode, TOS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TOS
Context triple: [Ostrowiec Świętokrzyski, carPlatesCode, TOS]
  • A. TOS
    TOS is an abbreviation that most commonly refers to "Terms of Service," the rules and conditions governing the use of a service or platform.
  • B. T.O.T.S.
    T.O.T.S. is an animated Disney Junior series that follows two delivery birds who transport baby animals to their families while learning lessons about friendship and responsibility.
  • C. TOG
    TOG is the commonly used abbreviation for The Open Group, an international consortium that develops open, vendor-neutral technology standards and certifications.
  • D. TSO
    TSO is a major Canadian symphony orchestra based in Toronto, renowned for its performances of classical and contemporary orchestral music.
  • E. TSO
    TSO (The Stationery Office) is a major UK publishing and information services company known for producing and distributing official government and public sector documents.
  • 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: TOS
Triple: [Ostrowiec Świętokrzyski, carPlatesCode, TOS]
Generated description
TOS is the vehicle registration code used on license plates for cars registered in Ostrowiec Świętokrzyski, Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TOS
Target entity description: TOS is the vehicle registration code used on license plates for cars registered in Ostrowiec Świętokrzyski, Poland.
  • A. TOS chosen
    TOS is an abbreviation that most commonly refers to "Terms of Service," the rules and conditions governing the use of a service or platform.
  • B. T.O.T.S.
    T.O.T.S. is an animated Disney Junior series that follows two delivery birds who transport baby animals to their families while learning lessons about friendship and responsibility.
  • C. TOG
    TOG is the commonly used abbreviation for The Open Group, an international consortium that develops open, vendor-neutral technology standards and certifications.
  • D. TSO
    TSO is a major Canadian symphony orchestra based in Toronto, renowned for its performances of classical and contemporary orchestral music.
  • E. TSO
    TSO (The Stationery Office) is a major UK publishing and information services company known for producing and distributing official government and public sector documents.
  • F. None of above.

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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58ffa6a481908866b6239d1d9b92 completed March 31, 2026, 11:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf28b78e90819098ab1d4877ab88fe completed April 3, 2026, 2:40 a.m.
NEDg Description generation batch_69cf2bd14c3c8190b43840ee57cca22c completed April 3, 2026, 2:54 a.m.
NED2 Entity disambiguation (via description) batch_69cf2cb3c4308190971fb3d25064f205 completed April 3, 2026, 2:57 a.m.
Created at: March 30, 2026, 6:35 p.m.