Triple
T22976299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanaa Lathan as Beneatha Younger |
E571327
|
entity |
| Predicate | characterOccupationAspiration |
P104631
|
FINISHED |
| Object | doctor |
—
|
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: doctor | Statement: [Sanaa Lathan as Beneatha Younger, characterOccupationAspiration, doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOccupationAspiration Context triple: [Sanaa Lathan as Beneatha Younger, characterOccupationAspiration, doctor]
-
A.
occupationAspiration
chosen
Indicates a person's desired or intended future occupation or career goal.
-
B.
subjectOccupation
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
C.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
D.
visionaryOccupation
Indicates that an entity holds an occupation or role characterized by forward-thinking, innovative, or visionary activities or responsibilities.
-
E.
targetCareer
Indicates that one entity is the intended or pursued career or professional goal of another entity.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182369b548190a6630655a6e0bb39 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:48 p.m.