Triple
T20602681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WB Games San Francisco |
E506221
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object | WB Games |
—
|
NE NERFINISHED |
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: WB Games | Statement: [WB Games San Francisco, brand, WB Games]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: WB Games Context triple: [WB Games San Francisco, brand, WB Games]
-
A.
WB Games San Francisco
chosen
WB Games San Francisco is a video game development studio under Warner Bros. Games known for creating mobile and online titles based on popular Warner Bros. entertainment franchises.
-
B.
WB Games Montréal
WB Games Montréal is a Canadian video game development studio best known for creating titles in the Batman: Arkham series and other DC Comics–based games.
-
C.
Activision Blizzard
Activision Blizzard is a major American video game holding company known for franchises such as Call of Duty, World of Warcraft, and Overwatch.
-
D.
SJ Games
SJ Games is a tabletop game publisher best known for producing titles like GURPS, Munchkin, and various strategy and role-playing games.
-
E.
Locomotive Games
Locomotive Games was a video game development studio known for working on licensed titles, including adaptations of popular film franchises.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa20f5c881909265ce7d96efc487 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:41 a.m.