Triple

T15338091
Position Surface form Disambiguated ID Type / Status
Subject Cheltenham Gold Cup E366719 entity
Predicate sponsor P67 FINISHED
Object Timico
Timico is a UK-based managed IT, cloud, and connectivity services provider known for its high-profile sports sponsorships, including horse racing events.
 E1151352 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: Timico | Statement: [Cheltenham Gold Cup, sponsor, Timico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Timico
Context triple: [Cheltenham Gold Cup, sponsor, Timico]
  • A. Tiko
    Tiko is a coastal town and port in southwestern Cameroon known for its agricultural activities and role as a transport hub.
  • B. Tabio
    Tabio is a small Colombian town in the department of Cundinamarca, known for its cool climate, agricultural traditions, and proximity to Bogotá.
  • C. Timolin
    Timolin is a given name most notably borne by Timolin Cole, one of the twin daughters of legendary American singer and pianist Nat King Cole.
  • D. Toshi
    Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
  • E. Tio
    Tio is a coastal town in Eritrea’s Southern Red Sea Region, known historically as a small port on the Red Sea.
  • 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: Timico
Triple: [Cheltenham Gold Cup, sponsor, Timico]
Generated description
Timico is a UK-based managed IT, cloud, and connectivity services provider known for its high-profile sports sponsorships, including horse racing events.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Timico
Target entity description: Timico is a UK-based managed IT, cloud, and connectivity services provider known for its high-profile sports sponsorships, including horse racing events.
  • A. Tiko
    Tiko is a coastal town and port in southwestern Cameroon known for its agricultural activities and role as a transport hub.
  • B. Tabio
    Tabio is a small Colombian town in the department of Cundinamarca, known for its cool climate, agricultural traditions, and proximity to Bogotá.
  • C. Timolin
    Timolin is a given name most notably borne by Timolin Cole, one of the twin daughters of legendary American singer and pianist Nat King Cole.
  • D. Toshi
    Toshi is a Japanese given name commonly used for both males and females, often as a short form of longer names such as Toshiro or Toshiko.
  • E. Tio
    Tio is a coastal town in Eritrea’s Southern Red Sea Region, known historically as a small port on the Red Sea.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e11b22c81908280efe65acd5454 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01f2ee9c819080fce24ed13a07c7 completed May 9, 2026, 9:44 a.m.
NEDg Description generation batch_69ff02a62dcc819087eddd2f0b4c29cb completed May 9, 2026, 9:47 a.m.
NED2 Entity disambiguation (via description) batch_69ff036153588190ae46fcde257eb3cb completed May 9, 2026, 9:50 a.m.
Created at: April 10, 2026, 3:17 a.m.