Triple
T26531711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-Louise von Franz |
E670836
|
entity |
| Predicate | meetingDateWithCarlJung |
P79179
|
FINISHED |
| Object | 1933 |
—
|
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: 1933 | Statement: [Marie-Louise von Franz, meetingDateWithCarlJung, 1933]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetingDateWithCarlJung Context triple: [Marie-Louise von Franz, meetingDateWithCarlJung, 1933]
-
A.
meetingDay
Indicates the specific day on which a meeting is scheduled or takes place between the related entities.
-
B.
dateOfFirstMeeting
chosen
Indicates the specific date on which two or more entities first met or came together.
-
C.
meetingPeriod
Indicates the time span or duration during which a meeting takes place.
-
D.
firstMeetingApproximateDate
Indicates an estimated or imprecise calendar date on which the first meeting between the related entities took place.
-
E.
meetsWhen
Indicates that two entities come together or encounter each other at a specific time or under particular temporal conditions.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f613f84cdc8190828985c94d8491d5 |
completed | May 2, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69f602d7b1b0819095ddd3b5169f8ce2 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 27, 2026, 1:36 a.m.