Triple
T22754813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Bewersdorf |
E562810
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | LOL |
—
|
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: LOL | Statement: [Kevin Bewersdorf, notableWork, LOL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LOL Context triple: [Kevin Bewersdorf, notableWork, LOL]
-
A.
LOL
chosen
LOL is a 2006 American independent mumblecore film directed by Joe Swanberg that explores modern relationships and digital communication.
-
B.
League of Legends
League of Legends is a popular multiplayer online battle arena (MOBA) video game developed by Riot Games, known for its competitive esports scene and strategic team-based gameplay.
-
C.
Runeterra
Runeterra is the richly detailed fantasy world that serves as the backdrop for the lore, champions, and stories of the League of Legends universe.
-
D.
Moonton
Moonton is a Chinese video game developer best known for creating the popular mobile multiplayer online battle arena game Mobile Legends: Bang Bang.
-
E.
LPL
LPL is the New York Stock Exchange ticker symbol for LG Display, a major South Korean manufacturer of display panels for TVs, monitors, and mobile devices.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179bc48788190b3deb9287d02cb2c |
completed | April 29, 2026, 3:23 a.m. |
Created at: April 17, 2026, 3:25 p.m.