Triple
T38276460
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camelot (2023 revival) |
E1021969
|
entity |
| Predicate | roleOfGueneverePlayedBy |
P192961
|
FINISHED |
| Object | Phillipa Soo |
—
|
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: Phillipa Soo | Statement: [Camelot (2023 revival), roleOfGueneverePlayedBy, Phillipa Soo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfGueneverePlayedBy Context triple: [Camelot (2023 revival), roleOfGueneverePlayedBy, Phillipa Soo]
-
A.
roleOfKingArthurPlayedBy
Indicates that the role or character of King Arthur is portrayed or performed by a particular actor or performer.
-
B.
helenaBonhamCarterRole
Indicates the acting role or character portrayed by Helena Bonham Carter in a work.
-
C.
JudithAndersonRole
Indicates that a role is one portrayed or performed by Judith Anderson.
-
D.
notableFemaleHero
Indicates that the subject is a female individual recognized for heroic actions or qualities that make her notably distinguished.
-
E.
fiancéePortrayedBy
Indicates that a character’s fiancée is depicted or played by a specific actor or performer.
- 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_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69fd328298ac8190b6bd5ded7dca270d |
completed | May 8, 2026, 12:46 a.m. |
Created at: May 3, 2026, 4:30 p.m.