Triple
T18669040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patti D'Arbanville |
E456418
|
entity |
| Predicate | startTimeOfCreativeCareer |
P132212
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [Patti D'Arbanville, startTimeOfCreativeCareer, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeOfCreativeCareer Context triple: [Patti D'Arbanville, startTimeOfCreativeCareer, 1960s]
-
A.
startTimeOfMusicCareer
Indicates the point in time when an entity’s music career began.
-
B.
startTimeOfProfessionalCareer
Indicates the point in time when an individual’s professional career formally begins.
-
C.
beganAmateurCareer
Indicates that an entity started its amateur-level career or involvement in a particular field or activity.
-
D.
beganBroadcastingCareer
Indicates that an entity started or initiated its professional career in broadcasting at a particular time or context.
-
E.
startedCareerAsChildActor
Indicates that a person began their professional career in acting during childhood.
- 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556b0502881909ea05f2746163746 |
completed | April 19, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484133ee48190a80f1889d79f34c9 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:48 a.m.