Triple
T30284285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand Maria Andrea Alfonso Marcus d’Aviano |
E770187
|
entity |
| Predicate | hasAncestralDynasty |
P57937
|
FINISHED |
| Object | House of Bourbon |
—
|
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: House of Bourbon | Statement: [Ferdinand Maria Andrea Alfonso Marcus d’Aviano, hasAncestralDynasty, House of Bourbon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAncestralDynasty Context triple: [Ferdinand Maria Andrea Alfonso Marcus d’Aviano, hasAncestralDynasty, House of Bourbon]
-
A.
isDynastic
Indicates that a relationship, status, or succession is based on or belongs to a hereditary ruling family or lineage.
-
B.
hasDynasticConnections
Indicates that one entity is related to another through familial or hereditary ties between ruling or noble dynasties.
-
C.
hasRoyalAncestryFrom
chosen
Indicates that one entity possesses royal lineage or descent originating from another entity.
-
D.
hasDynast
Indicates that an entity is associated with or ruled by a particular dynasty.
-
E.
belongsToDynasticHistory
Indicates that something is part of, or associated with, a particular dynastic historical period or lineage.
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 29, 2026, 7:45 p.m.