Triple
T12421081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Russell |
E296772
|
entity |
| Predicate | characterOccupationPortrayed |
P56368
|
FINISHED |
| Object | science 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: science teacher | Statement: [William Russell, characterOccupationPortrayed, science teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOccupationPortrayed Context triple: [William Russell, characterOccupationPortrayed, science teacher]
-
A.
characterPortrayedIs
Indicates that one entity serves as the fictional or dramatic role that is depicted or played by another entity.
-
B.
portrayedByProfession
Indicates that an entity is depicted or represented by someone acting in a specified professional capacity.
-
C.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
D.
notableCharacterOccupation
chosen
Indicates that a notable character is associated with a specific occupation or professional role.
-
E.
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.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.