Triple
T3157677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raptors Uprising GC |
E66024
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | Toronto Raptors esports |
E23263
|
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: Toronto Raptors esports | Statement: [Raptors Uprising GC, brand, Toronto Raptors esports]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toronto Raptors esports Context triple: [Raptors Uprising GC, brand, Toronto Raptors esports]
-
A.
Toronto Raptors
chosen
The Toronto Raptors are a professional Canadian basketball team based in Toronto that competes in the NBA and won their first championship in 2019.
-
B.
Knicks Gaming
Knicks Gaming is the official NBA 2K League esports team affiliated with the New York Knicks.
-
C.
Pacers Gaming
Pacers Gaming is the official NBA 2K League esports team affiliated with the Indiana Pacers organization.
-
D.
Toronto Rocket
The Toronto Rocket is a modern, fully accessible subway train series used by the Toronto Transit Commission on its heavy rail lines.
-
E.
Nets Gaming Crew
Nets Gaming Crew is a professional NBA 2K League esports team affiliated with the Brooklyn Nets.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ad85850c1481908a9e9c6242238de2 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5ec0da88190a83f3448ac76e98e |
completed | March 8, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2250a682c8190b01e949f27d6932e |
completed | March 12, 2026, 2:29 a.m. |
Created at: March 8, 2026, 3:05 p.m.