Triple
T9767920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Sher |
E237044
|
entity |
| Predicate | workedOn |
P3
|
FINISHED |
| Object | Joker |
E38375
|
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: Joker | Statement: [Lawrence Sher, workedOn, Joker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joker Context triple: [Lawrence Sher, workedOn, Joker]
-
A.
Joker
chosen
Joker is a 2019 psychological thriller film centered on the origin story of Batman’s iconic nemesis, depicting his descent into madness and violence in a gritty, character-driven narrative.
-
B.
Joker
Joker is the masked protagonist of Persona 5, a stylish phantom thief who leads the Phantom Thieves of Hearts and wields dual personas in battle.
-
C.
Joker
Joker is a DC Comics–themed roller coaster at Six Flags México known for its chaotic, unpredictable ride experience.
-
D.
Joker
Joker is a skilled and wisecracking pilot in the Mass Effect video game series, known for flying the Normandy and providing comic relief.
-
E.
Joker
Joker is the popular nickname of Serbian NBA superstar Nikola Jokić, a dominant, playmaking center for the Denver Nuggets.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a2da648190836916a45d2998d7 |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c412f0a48190b59d030b703a0e45 |
completed | April 5, 2026, 2:08 a.m. |
Created at: March 30, 2026, 8:25 p.m.