Triple
T5218323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eleonor Magdalene of Neuburg |
E117806
|
entity |
| Predicate | chronologicalOrderAsSpouse |
P4764
|
FINISHED |
| Object | third wife of Leopold I, Holy Roman Emperor |
—
|
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: third wife of Leopold I, Holy Roman Emperor | Statement: [Eleonor Magdalene of Neuburg, chronologicalOrderAsSpouse, third wife of Leopold I, Holy Roman Emperor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalOrderAsSpouse Context triple: [Eleonor Magdalene of Neuburg, chronologicalOrderAsSpouse, third wife of Leopold I, Holy Roman Emperor]
-
A.
metSpouseAt
Indicates that one person first encountered or became acquainted with their spouse at a particular place, event, or time.
-
B.
spouseOrder
chosen
Indicates the position or sequence of a person among multiple spouses in a marital relationship.
-
C.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
D.
spouseAlsoKnownAs
Indicates that a person’s spouse is referred to by an alternative name or alias.
-
E.
hasSpouseInStory
Indicates that one entity is depicted as the spouse of another within the context of a particular story or narrative.
- 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_69bd4465e03081909bfcfd7113062590 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a96d49c8190a58726a57edebdcc |
completed | March 20, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69bd77bd2a448190a9ae5afd2585a7b9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:48 p.m.