Triple
T28017297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Mancini |
E707581
|
entity |
| Predicate | relatedVia |
P141717
|
FINISHED |
| Object | Mazarin nieces |
—
|
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: Mazarin nieces | Statement: [House of Mancini, relatedVia, Mazarin nieces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedVia Context triple: [House of Mancini, relatedVia, Mazarin nieces]
-
A.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
B.
associatedThrough
chosen
Indicates that two entities are connected or related to each other by means of a specified intermediary, context, or linkage.
-
C.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
D.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
E.
relatedIntermediate
Indicates an indirect or intermediate relationship between two entities, typically via one or more other entities or steps rather than a direct connection.
- 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69ffb5c373948190a6606e8caa87a384 |
completed | May 9, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ffb261da788190b41399df8ed895e8 |
completed | May 9, 2026, 10:17 p.m. |
Created at: April 27, 2026, 8:07 p.m.