Triple
T19882415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsieur Beaucaire |
E477808
|
entity |
| Predicate | hasFictionalNobleTitle |
P914
|
FINISHED |
| Object | French nobleman |
—
|
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: French nobleman | Statement: [Monsieur Beaucaire, hasFictionalNobleTitle, French nobleman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalNobleTitle Context triple: [Monsieur Beaucaire, hasFictionalNobleTitle, French nobleman]
-
A.
hasHonoraryTitle
Indicates that an entity has been granted a formal honorary title or distinction, typically in recognition of merit or achievement.
-
B.
nobleTitleAcquiredThrough
Indicates the manner, event, or process by which a person comes to obtain or be granted a particular noble title.
-
C.
nobleTitleOrStatus
Indicates that one entity holds, claims, or is associated with a particular noble rank, title, or social status in relation to another entity.
-
D.
usesRoyalTitle
Indicates that one entity refers to another using a royal title or honorific (such as king, queen, prince, or similar).
-
E.
associatedNobleTitle
chosen
Indicates that an entity is linked to or bears a particular noble or aristocratic 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658e0ccc88190b6f093035cd6f2a1 |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:52 p.m.