Triple

T28005195
Position Surface form Disambiguated ID Type / Status
Subject FIFA Global Series E707256 entity
Predicate usesGameMode P69305 FINISHED
Object FIFA Ultimate Team
FIFA Ultimate Team is a popular online game mode in the FIFA series where players build custom squads using virtual player cards to compete in various competitive and cooperative matches.
E1799949 NE FINISHED

How this triple was built (2 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: FIFA Ultimate Team | Statement: [FIFA Global Series, usesGameMode, FIFA Ultimate Team]
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: FIFA Ultimate Team
Triple: [FIFA Global Series, usesGameMode, FIFA Ultimate Team]
Generated description
FIFA Ultimate Team is a popular online game mode in the FIFA series where players build custom squads using virtual player cards to compete in various competitive and cooperative matches.

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_69ef96ba350c81908230d0b501b974c4 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63bd4e25c81909b4a26577a4a5479 completed May 2, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a15b89ab048819084f5a834a67da851 completed May 26, 2026, 3:13 p.m.
NEDg Description generation batch_6a15bc64012c819080a6cc815ad19ff8 completed May 26, 2026, 3:29 p.m.
NED2 Entity disambiguation (via description) batch_6a15bd0bb30c8190b4cce0b94f4efcac completed May 26, 2026, 3:32 p.m.
Created at: April 27, 2026, 7:59 p.m.