Triple
T20541986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura Wright |
E504361
|
entity |
| Predicate | startTimeOfRoleCarlyCorinthosOnGeneralHospital |
P140475
|
FINISHED |
| Object | 2005 |
—
|
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: 2005 | Statement: [Laura Wright, startTimeOfRoleCarlyCorinthosOnGeneralHospital, 2005]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfRoleCarlyCorinthosOnGeneralHospital Context triple: [Laura Wright, startTimeOfRoleCarlyCorinthosOnGeneralHospital, 2005]
-
A.
startTimeOfRole_Regine Hunter
Indicates the point in time when the role associated with Regine Hunter begins.
-
B.
endTimeOfRole_Regine Hunter
Indicates the point in time when Regine Hunter’s role or position comes to an end.
-
C.
startTimeOfRelationshipWithCharlizeTheron
Indicates the point in time when a relationship with Charlize Theron began.
-
D.
startedRoleAsKimHughes
Indicates that an entity began performing or assuming the role of Kim Hughes.
-
E.
characterPlayedByKathleenQuinlan
Indicates that a given character is portrayed or acted by Kathleen Quinlan.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a292dd1c8190b5c3031f3b44eb52 |
completed | April 20, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:37 a.m.