Triple
T28896818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Tobias |
E732854
|
entity |
| Predicate | roleInMortalKombat |
P197621
|
FINISHED |
| Object | lead designer |
—
|
LITERAL 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: lead designer | Statement: [John Tobias, roleInMortalKombat, lead designer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInMortalKombat Context triple: [John Tobias, roleInMortalKombat, lead designer]
-
A.
roleInMonsterVerse
Indicates that an entity has a specific role or function within the MonsterVerse franchise or universe.
-
B.
roleInCobraKai
Indicates that an entity has a specific role or position within the context of Cobra Kai.
-
C.
roleInKungFuPanda3
Indicates that an entity participated in the movie "Kung Fu Panda 3" in a specific role (such as actor, voice actor, or production role).
-
D.
smashBrosRole
Indicates that one entity has a specific role or function related to the Super Smash Bros. game or its competitive context in relation to another entity.
-
E.
wrestlingRole
Indicates the specific capacity or function an individual performs within a wrestling context, such as competitor, referee, coach, or other defined role.
- F. None of above. chosen
Provenance (4 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
| PDg | Predicate description generation | batch_69fe9fb88db08190a8f4af350633330e |
completed | May 9, 2026, 2:45 a.m. |
Created at: April 28, 2026, 7:59 a.m.