Triple
T35975983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Walter Grindlay Simpson |
E1040415
|
entity |
| Predicate | modeledAsCharacterIn |
P177716
|
FINISHED |
| Object | An Inland Voyage |
—
|
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: An Inland Voyage | Statement: [Sir Walter Grindlay Simpson, modeledAsCharacterIn, An Inland Voyage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modeledAsCharacterIn Context triple: [Sir Walter Grindlay Simpson, modeledAsCharacterIn, An Inland Voyage]
-
A.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
-
B.
playedRoleIn
Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
-
C.
hasPortrayedRole
Indicates that an entity has performed or depicted a specific role or character, typically in a work such as a film, play, or television show.
-
D.
isPortrayedIn
chosen
Indicates that an entity is depicted or represented within a particular work, medium, or portrayal.
-
E.
hasPortrayedPersonRole
Indicates that an entity has performed or held a specific role in portraying a particular person (e.g., in a film, play, or other representation).
- 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_69f76e27758c81909b711cf38a130aaf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7acaec1508190a38f2ac9cc5383e7 |
completed | May 3, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f7ab75387c819091afc3c2128eb903 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.