Triple
T28953905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patty Uris |
E731097
|
entity |
| Predicate | relationshipToStanUris |
P108204
|
FINISHED |
| Object | wife |
—
|
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: wife | Statement: [Patty Uris, relationshipToStanUris, wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToStanUris Context triple: [Patty Uris, relationshipToStanUris, wife]
-
A.
relationshipToUniversity
Indicates the type or nature of a person's or entity's connection or affiliation with a specific university.
-
B.
relationshipToStanley
chosen
Indicates the specific type of personal or social relationship an entity has with Stanley.
-
C.
relationshipToStevens
Indicates a specified type of relationship that an entity has to the person or entity named Stevens.
-
D.
relationshipTypeWithStevens
Indicates the specific nature or category of the relationship that an entity has with Stevens.
-
E.
relationshipToStudents
Indicates the type or nature of connection one entity has with students, such as role, affiliation, or responsibility toward them.
- 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_69f043eb9bcc819091ac7b07aecb6475 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_6a00a602b6b48190a9dea8ae22d2fa05 |
completed | May 10, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_6a00a559bf3881909a7b50776d8f47bb |
completed | May 10, 2026, 3:33 p.m. |
Created at: April 28, 2026, 8:45 a.m.