Triple
T2519489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viceroy of Naples |
E55487
|
entity |
| Predicate | officeHolderCharacteristic |
P5316
|
FINISHED |
| Object | usually a high-ranking Spanish noble |
—
|
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: usually a high-ranking Spanish noble | Statement: [Viceroy of Naples, officeHolderCharacteristic, usually a high-ranking Spanish noble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeHolderCharacteristic Context triple: [Viceroy of Naples, officeHolderCharacteristic, usually a high-ranking Spanish noble]
-
A.
officeHolderOf
Indicates that a person holds or has held an official position or role within a specified organization, institution, or office.
-
B.
hasPoliticalCharacteristic
chosen
Indicates that an entity possesses a specific political attribute, quality, or affiliation.
-
C.
officeHolderUsually
Indicates that an entity is the person who typically or customarily holds a particular office or position.
-
D.
officeHolderMayBe
Indicates that a specified person is permitted or eligible to hold a particular office or position.
-
E.
officeHolderRoleFor
Indicates that a specific role or position is held by an office holder within an organization or governing body.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0bf37c0819088d28b5081ba7556 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.