Triple

T6536667
Position Surface form Disambiguated ID Type / Status
Subject Joseph Reed E168180 entity
Predicate hasPartnershipWith P1136 FINISHED
Object Tappin
Tappin is a professional collaborator or business partner associated with Joseph Reed.
E605723 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: Tappin | Statement: [Joseph Reed, hasPartnershipWith, Tappin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tappin
Context triple: [Joseph Reed, hasPartnershipWith, Tappin]
  • A. Tip and Tap
    Tip and Tap are the twin boy mascots created to represent West Germany as the official characters of the 1974 FIFA World Cup.
  • B. Tuktukan
    Tuktukan is a barangay (village-level administrative division) in the city of Taguig in Metro Manila, Philippines.
  • C. Tappara
    Tappara is a prominent professional ice hockey club from Tampere, Finland, known as one of the most successful and historic teams in the Finnish Liiga.
  • D. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • E. Tarouca
    Tarouca is a municipality in Portugal’s Douro region, known for its historic monasteries, vineyards, and scenic river valley landscapes.
  • 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: Tappin
Triple: [Joseph Reed, hasPartnershipWith, Tappin]
Generated description
Tappin is a professional collaborator or business partner associated with Joseph Reed.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tappin
Target entity description: Tappin is a professional collaborator or business partner associated with Joseph Reed.
  • A. Tip and Tap
    Tip and Tap are the twin boy mascots created to represent West Germany as the official characters of the 1974 FIFA World Cup.
  • B. Tuktukan
    Tuktukan is a barangay (village-level administrative division) in the city of Taguig in Metro Manila, Philippines.
  • C. Tappara
    Tappara is a prominent professional ice hockey club from Tampere, Finland, known as one of the most successful and historic teams in the Finnish Liiga.
  • D. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • E. Tarouca
    Tarouca is a municipality in Portugal’s Douro region, known for its historic monasteries, vineyards, and scenic river valley landscapes.
  • 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_69c68a51564081909e93aee0dbd9cca3 completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6add33acc8190bb0a9531648198f2 completed March 27, 2026, 4:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d53616848190835d9f02bd8e2dbf completed March 27, 2026, 7:06 p.m.
NEDg Description generation batch_69c6d6dad26481908ac4bc0ed703091b completed March 27, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69c6d833d84c819083ffc81bda7d35d4 completed March 27, 2026, 7:19 p.m.
Created at: March 27, 2026, 1:49 p.m.