Triple
T26194798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scatcherd |
E655068
|
entity |
| Predicate | hasNotableBearerFictional |
P7927
|
FINISHED |
| Object | Sir Roger Scatcherd |
—
|
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: Sir Roger Scatcherd | Statement: [Scatcherd, hasNotableBearerFictional, Sir Roger Scatcherd]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableBearerFictional Context triple: [Scatcherd, hasNotableBearerFictional, Sir Roger Scatcherd]
-
A.
hasNotableFictionalBearer
chosen
Indicates that an entity is associated with at least one well-known fictional character that bears its name or designation.
-
B.
isFictionalBearer
Indicates that an entity serves as the (typically named) holder or possessor of something within a fictional or imaginary context.
-
C.
hasNotableFable
Indicates that an entity is associated with a well-known or significant fable, either as its subject, source, or key element.
-
D.
hasFictionalAuthor
Indicates that one entity is the fictional or in-universe author of a work attributed to them.
-
E.
hasNotableBearerTitle
Indicates that an entity is associated with a notable person or group who holds a specific title or designation.
- 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69fd05ba6b2c81909c62b46237d10365 |
completed | May 7, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69fd03039e48819082b6e12c5453885a |
completed | May 7, 2026, 9:24 p.m. |
Created at: April 26, 2026, 8:46 p.m.