Triple
T8175798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | We Global |
E190933
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object | Brisco |
E716269
|
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: Brisco | Statement: [We Global, featuresArtist, Brisco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brisco Context triple: [We Global, featuresArtist, Brisco]
-
A.
Brisco
chosen
Brisco is an American rapper known for his collaborations with prominent hip-hop artists and appearances on DJ Khaled’s We the Best projects.
-
B.
Hoyle
Hoyle is a surname of English origin borne by various notable individuals across politics, science, and the arts.
-
C.
Solitaire
Solitaire is a classic single-player card game that became widely known through its inclusion as a standard game on early Microsoft Windows operating systems.
-
D.
Solitaire
Solitaire is a fictional psychic tarot reader and Bond girl who appears as a key ally and love interest to James Bond in the novel and film "Live and Let Die."
-
E.
Big Two
Big Two is a popular East Asian shedding-type card game, especially common in Chinese communities, where players race to be the first to discard all their cards using poker-like combinations.
- 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_69ca82c1c0a08190bf8692b4d91a03ca |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4ab8295081909a450fcaa34f6ec6 |
completed | March 31, 2026, 4:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cced64c9588190b8db6452c364347d |
completed | April 1, 2026, 10:03 a.m. |
Created at: March 30, 2026, 5:40 p.m.