Triple
T3484019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marta Helena Skowrońska |
E73563
|
entity |
| Predicate | earlyOccupation |
P49040
|
FINISHED |
| Object | servant |
—
|
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: servant | Statement: [Marta Helena Skowrońska, earlyOccupation, servant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earlyOccupation Context triple: [Marta Helena Skowrońska, earlyOccupation, servant]
-
A.
earliestOccupation
Indicates that the associated occupation is the first or earliest known job or professional role held by the person in question.
-
B.
earlierOccupation
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
C.
traditionalOccupations
Indicates that an entity is associated with occupations or jobs that are customary, long-established, or culturally traditional within a particular community or context.
-
D.
occupationBegan
Indicates the point in time when an entity started holding a particular occupation or job.
-
E.
earliestOccupationDate
Indicates the earliest known date on which an entity began a particular occupation or role.
- 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_69ad85b3c9b08190857cae74c7f36da9 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb795db88190805b26d9774fdb73 |
completed | March 8, 2026, 6:10 p.m. |
| PD | Predicate disambiguation | batch_69adae0935ac8190bfa8a8bd3dcd3301 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb1ecb02881908394f197e31431b4 |
completed | March 8, 2026, 5:29 p.m. |
Created at: March 8, 2026, 3:17 p.m.