Triple
T5013361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Scicolone |
E112679
|
entity |
| Predicate | siblingRelationshipTo |
P363
|
FINISHED |
| Object | younger sister of Sophia Loren |
—
|
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: younger sister of Sophia Loren | Statement: [Maria Scicolone, siblingRelationshipTo, younger sister of Sophia Loren]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: siblingRelationshipTo Context triple: [Maria Scicolone, siblingRelationshipTo, younger sister of Sophia Loren]
-
A.
sibling
chosen
Indicates that two entities share at least one parent, making them brothers or sisters to each other.
-
B.
stepSibling
Indicates that two people share at least one parent but do not share both biological parents, making them step-siblings.
-
C.
basisOfRelationship
Indicates that one entity serves as the foundational reason, cause, or justification for the relationship that exists between two or more entities.
-
D.
hasFamilialTieTo
Indicates a relationship where two entities are connected by family bonds, such as by blood, marriage, or adoption.
-
E.
laterRelationWith
Indicates that one entity stands in a temporal relationship to another such that it occurs or exists at a later time than the other.
- 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7310c5b08190a5c9ab0f9fe9569f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.