Triple
T16229018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Substitute |
E393929
|
entity |
| Predicate | leadCharacterCoverOccupation |
P21567
|
FINISHED |
| Object | substitute teacher |
—
|
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: substitute teacher | Statement: [The Substitute, leadCharacterCoverOccupation, substitute teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterCoverOccupation Context triple: [The Substitute, leadCharacterCoverOccupation, substitute teacher]
-
A.
leadActorOccupation
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
B.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
C.
followsCharacterOccupation
Indicates that one character’s occupation or job role comes after or succeeds another character’s occupation in a sequence or progression.
-
D.
coverRole
Indicates that one entity temporarily assumes or fills the role, duties, or position normally held by another entity.
-
E.
characterCoverIdentity
Indicates that one character uses another identity as a cover or disguise, typically concealing their true identity.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2889688190ac04e4e9479cabf4 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:03 a.m.