Triple
T31007412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gail Dwyer |
E790106
|
entity |
| Predicate | hasOnScreenOccupation |
P179248
|
FINISHED |
| Object | 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: teacher | Statement: [Gail Dwyer, hasOnScreenOccupation, teacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenOccupation Context triple: [Gail Dwyer, hasOnScreenOccupation, teacher]
-
A.
hasOnScreenOwner
Indicates that an entity is owned or controlled by another entity that is explicitly shown or represented on screen.
-
B.
hasOnScreenConflictWith
Indicates that two entities are depicted as being in conflict or opposition with each other within an on-screen or visual context.
-
C.
hasOnScreenDynamic
Indicates that one entity displays or presents another entity as a changing or interactive element on a screen.
-
D.
hasRelativeOccupation
Indicates that two people are related in such a way that one’s occupation is defined or characterized in relation to the other’s occupation.
-
E.
hasScreen
Indicates that an entity is equipped with or includes a screen or display component.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7201e241c819092d56a7bb99dc94d |
completed | May 3, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
| PDg | Predicate description generation | batch_69f71f8df5d48190944fbfbd9d573868 |
completed | May 3, 2026, 10:12 a.m. |
Created at: April 29, 2026, 8:57 p.m.