Triple
T25118364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabella de Jode |
E629194
|
entity |
| Predicate | spouse place of activity |
P73253
|
FINISHED |
| Object | Antwerp |
—
|
NE NERFINISHED |
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: Antwerp | Statement: [Isabella de Jode, spouse place of activity, Antwerp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouse place of activity Context triple: [Isabella de Jode, spouse place of activity, Antwerp]
-
A.
spousePlaceOfWork
chosen
Indicates that the place of work specified belongs to the spouse of the referenced person.
-
B.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
-
C.
spouseInWork
Indicates that two entities are spouses within the context of a particular work (such as a book, film, or series), rather than in real life.
-
D.
spouseOfWork
Indicates that one person is the spouse of another specifically in the context of their workplace or professional environment.
-
E.
spousePoliticalActivity
Indicates that one person’s spouse engages in political actions, involvement, or advocacy connected to that person or their role.
- 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_69e2ff3169d08190973b6061d5009abd |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 6:27 a.m.