Triple
T32604536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert de Boron |
E833471
|
entity |
| Predicate | portrayedMerlinAs |
P55200
|
FINISHED |
| Object | prophet |
—
|
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: prophet | Statement: [Robert de Boron, portrayedMerlinAs, prophet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedMerlinAs Context triple: [Robert de Boron, portrayedMerlinAs, prophet]
-
A.
roleOfKingArthurPlayedBy
Indicates that the role or character of King Arthur is portrayed or performed by a particular actor or performer.
-
B.
roleOfLancelotPlayedBy
Indicates that a person is the actor who portrays the character Lancelot in a performance or production.
-
C.
roleOfGueneverePlayedBy
Indicates that a specified person or performer portrays the character Guenevere in a production or performance.
-
D.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
E.
wasPortrayedAs
chosen
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe78e545888190a239af1a84280fa0 |
completed | May 8, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69fe7842742081908043eb950ed69f92 |
completed | May 8, 2026, 11:56 p.m. |
Created at: May 1, 2026, 1:05 a.m.