Triple
T33775227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oathkeeper |
E865496
|
entity |
| Predicate | tvPortrayalProp |
P37849
|
FINISHED |
| Object | Game of Thrones TV series |
—
|
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: Game of Thrones TV series | Statement: [Oathkeeper, tvPortrayalProp, Game of Thrones TV series]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tvPortrayalProp Context triple: [Oathkeeper, tvPortrayalProp, Game of Thrones TV series]
-
A.
portrayedVia
chosen
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
B.
notableSceneProp
Indicates that an object or element serves as a significant or prominently featured prop within a particular scene.
-
C.
starPortrays
Indicates that a person has a starring role in which they portray a particular character in a work.
-
D.
stagePortrayalIncludes
Indicates that a stage portrayal incorporates or features a particular element, character, action, or aspect within the performance.
-
E.
motherPortrayedBy
Indicates that a person’s mother is depicted or played by a particular actor or performer.
- F. None of above.
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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:45 a.m.