Triple
T15224095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Sianis |
E363831
|
entity |
| Predicate | Sam SianisRelationship |
P117615
|
FINISHED |
| Object | nephew |
—
|
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: nephew | Statement: [William Sianis, Sam SianisRelationship, nephew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Sam SianisRelationship Context triple: [William Sianis, Sam SianisRelationship, nephew]
-
A.
relationshipTypeWithSamMalone
Indicates the specific nature or category of relationship that an entity has with Sam Malone.
-
B.
relationshipToSissySullivan
Indicates the specific familial, social, or personal relationship that one entity has to Sissy Sullivan.
-
C.
relationshipToSamBaldwin
Indicates the specific type of relationship or connection an entity has to Sam Baldwin.
-
D.
relationshipTypeWith Alicia Johns
Indicates the specific type or nature of the relationship that an entity has with Alicia Johns.
-
E.
relationshipTypeWithStephanie Ramzinski
Indicates the specific nature or category of relationship that an entity has with Stephanie Ramzinski.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078a9318819081db3b7bcc28e04f |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:12 a.m.