Triple
T36036020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Italian Key |
E1042399
|
entity |
| Predicate | hasInheritanceMotif |
P202562
|
FINISHED |
| Object | seaside estate |
—
|
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: seaside estate | Statement: [The Italian Key, hasInheritanceMotif, seaside estate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInheritanceMotif Context triple: [The Italian Key, hasInheritanceMotif, seaside estate]
-
A.
hasTypeOfMotif
Indicates that one entity features or is characterized by a specific kind or category of motif.
-
B.
hasInheritanceModel
Indicates that one entity is associated with a specific pattern or scheme by which traits, properties, or characteristics are passed from one generation or source to another.
-
C.
hasInheritanceRule
Indicates that a specific rule or policy governs how rights, properties, or attributes are passed from one entity to another.
-
D.
hasMirrorMotif
Indicates that one entity features a mirror-related motif or pattern in relation to another entity or context.
-
E.
isInherited
Indicates that one entity derives its characteristics, properties, or rights from another through an inheritance relationship.
- 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_69f76e2d7e8c8190bac4e90734566799 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a0091ad8b8c8190b0f00a3358e59bc1 |
completed | May 10, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_6a008f2813ec81909a54c2dfa5c75dc7 |
completed | May 10, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_6a0091ac9ff08190b635eac6aa3f6128 |
completed | May 10, 2026, 2:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.