Triple
T38276461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camelot (2023 revival) |
E1021969
|
entity |
| Predicate | roleOfLancelotPlayedBy |
P193037
|
FINISHED |
| Object | Jordan Donica |
—
|
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: Jordan Donica | Statement: [Camelot (2023 revival), roleOfLancelotPlayedBy, Jordan Donica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfLancelotPlayedBy Context triple: [Camelot (2023 revival), roleOfLancelotPlayedBy, Jordan Donica]
-
A.
roleOfKingArthurPlayedBy
Indicates that the role or character of King Arthur is portrayed or performed by a particular actor or performer.
-
B.
roleOfGueneverePlayedBy
Indicates that a specified person or performer portrays the character Guenevere in a production or performance.
-
C.
LancastrianCommander
Indicates that the subject serves as a military commander aligned with the Lancastrian side in the Wars of the Roses.
-
D.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
E.
GameOfThronesRole
Indicates that one entity plays, voices, or otherwise portrays a character in the television series "Game of Thrones" in relation to another entity.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
| PDg | Predicate description generation | batch_69fd35d029588190a525aa8a506e7708 |
completed | May 8, 2026, 1:01 a.m. |
Created at: May 3, 2026, 4:30 p.m.