Triple
T25544312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bel-imperia |
E640254
|
entity |
| Predicate | relativeTypeToLorenzo |
P43530
|
FINISHED |
| Object | sister |
—
|
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: sister | Statement: [Bel-imperia, relativeTypeToLorenzo, sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeTypeToLorenzo Context triple: [Bel-imperia, relativeTypeToLorenzo, sister]
-
A.
hasRelationshipTypeWith Philippe Renaldo
Indicates that there exists a specific type or category of relationship between an entity and Philippe Renaldo.
-
B.
relationshipToTheDude
Indicates the specific type of personal or social relationship that one entity has to the individual referred to as "the Dude."
-
C.
relationToVonMaur
Indicates a specified type of relationship or association that an entity has with Von Maur.
-
D.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
E.
relatedType
chosen
Indicates that one entity is connected to another through a specified type or category of relationship.
- 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_69e75dbfff7081909b0aa779d48321d2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 21, 2026, 3:27 p.m.