Triple
T18404141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deirdre Lovejoy |
E450074
|
entity |
| Predicate | characterOccupationOfNotableRole |
P56368
|
FINISHED |
| Object | Assistant State's Attorney |
—
|
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: Assistant State's Attorney | Statement: [Deirdre Lovejoy, characterOccupationOfNotableRole, Assistant State's Attorney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterOccupationOfNotableRole Context triple: [Deirdre Lovejoy, characterOccupationOfNotableRole, Assistant State's Attorney]
-
A.
notableCharacterOccupation
chosen
Indicates that a notable character is associated with a specific occupation or professional role.
-
B.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
C.
notableWorkCharacter
Indicates that a character appears in, is associated with, or plays a role in a particular notable work.
-
D.
namedPersonRole
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
E.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
- 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_69d8b9fab8a8819086a9ddc0871715e0 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e5195509cc8190bd4e91adb9b4a0ce |
completed | April 19, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e469bf7f74819096a01173493412c2 |
completed | April 19, 2026, 5:35 a.m. |
Created at: April 10, 2026, 10:46 a.m.