Triple
T35432016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monegasque monarchy |
E1024086
|
entity |
| Predicate | usesTitleForConsort |
P192250
|
FINISHED |
| Object | Princess of Monaco |
—
|
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: Princess of Monaco | Statement: [Monegasque monarchy, usesTitleForConsort, Princess of Monaco]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTitleForConsort Context triple: [Monegasque monarchy, usesTitleForConsort, Princess of Monaco]
-
A.
usesTitleIn
Indicates that an entity is referred to using a particular title within a specified context or medium.
-
B.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
C.
usedTitleIn
Indicates that one entity employed or referenced another entity as a title in some context.
-
D.
usedTitleFrom
Indicates that one entity has employed or adopted the title originating from another entity.
-
E.
isTitleForInstitution
Indicates that a given title or designation is formally associated with or used by a particular institution.
- 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_69f76df743c48190aecb6dd79efb0d95 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
| PDg | Predicate description generation | batch_69fd026757a081909911a59a78652709 |
completed | May 7, 2026, 9:21 p.m. |
Created at: May 3, 2026, 4:03 p.m.