Triple
T9936497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beverly Marsh |
E192771
|
entity |
| Predicate | occupationAsAdult |
P2374
|
FINISHED |
| Object | fashion designer |
—
|
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: fashion designer | Statement: [Beverly Marsh, occupationAsAdult, fashion designer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupationAsAdult Context triple: [Beverly Marsh, occupationAsAdult, fashion designer]
-
A.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
B.
occupationType
Indicates the specific kind or category of work, profession, or role that an entity performs or holds.
-
C.
latestOccupation
Indicates the most recent job, role, or position that an entity currently holds or last held.
-
D.
representedOccupation
Indicates that one entity has served as an official or formal representative of another entity’s occupation or professional role.
-
E.
occupationDuringAlias
Indicates that an entity held a particular occupation specifically during the time period when it was known by a given alias.
- 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_69ca82dd978c8190947124ab0d3315ac |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb5e3bfa88190a88f20f2687a2583 |
completed | April 2, 2026, 12:18 a.m. |
| PD | Predicate disambiguation | batch_69cd1d9428cc81909b4b4938566d78a7 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:44 p.m.