Triple
T23863369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Parma (consort) |
E592509
|
entity |
| Predicate | titleHolderMarriagePlace |
P27490
|
FINISHED |
| Object | Rome |
—
|
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: Rome | Statement: [Duchess of Parma (consort), titleHolderMarriagePlace, Rome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderMarriagePlace Context triple: [Duchess of Parma (consort), titleHolderMarriagePlace, Rome]
-
A.
titleHolderMarriageCelebrationCountry
Indicates the country where the title holder’s marriage celebration took place.
-
B.
betrothalOrMarriagePlace
Indicates the location where a betrothal or marriage event takes place.
-
C.
marriageLocation
chosen
Indicates the place where a marriage ceremony or legal union between two people took place.
-
D.
marriageDocumentedIn
Indicates that a marriage event is recorded or evidenced in a specific document or source.
-
E.
titleHolderSpouseInstanceOf
Indicates that the spouse of a title holder is an instance of a specified role, status, or class related to that title.
- 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_69e25d22eb488190914b193aff952e83 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1cae16df4819081a8b3a395e45118 |
completed | April 29, 2026, 9:09 a.m. |
| PD | Predicate disambiguation | batch_69f1614a65a88190bde1efb368a151e4 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:13 p.m.