Triple
T26282324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cleaning Lady |
E661030
|
entity |
| Predicate | protagonistCurrentCoverOccupation |
P21567
|
FINISHED |
| Object | cleaning lady |
—
|
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: cleaning lady | Statement: [The Cleaning Lady, protagonistCurrentCoverOccupation, cleaning lady]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistCurrentCoverOccupation Context triple: [The Cleaning Lady, protagonistCurrentCoverOccupation, cleaning lady]
-
A.
featuresProtagonistOccupation
chosen
Indicates that the work’s main character has a specified occupation or job role.
-
B.
otherProtagonistOccupation
Indicates that another main character in the narrative has a specific occupation or job role.
-
C.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
D.
currentPrimaryRole
Indicates the role an entity is presently holding as its main or most important function or position.
-
E.
proposerOccupation
Indicates the occupation or professional role held by the entity acting as the proposer in a given context.
- 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_69ee812bbd448190be4d7478b057990a |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60e74cdf08190b753c3c10691a440 |
completed | May 2, 2026, 2:47 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 26, 2026, 10:01 p.m.