Triple
T7070782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robyn Smith |
E164687
|
entity |
| Predicate | relativeAgeDifferenceWithSpouse |
P47587
|
FINISHED |
| Object | much younger than Fred Astaire |
—
|
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: much younger than Fred Astaire | Statement: [Robyn Smith, relativeAgeDifferenceWithSpouse, much younger than Fred Astaire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relativeAgeDifferenceWithSpouse Context triple: [Robyn Smith, relativeAgeDifferenceWithSpouse, much younger than Fred Astaire]
-
A.
spouseAgeDifference
chosen
Indicates the age gap between two individuals who are spouses in a marital relationship.
-
B.
spouseOfSince
Indicates that two individuals are spouses and specifies the date or time from which their marital relationship has been in effect.
-
C.
spouseInstanceOf
Indicates that one entity is the specific spouse (marriage partner) instance of another entity.
-
D.
spouseAssociatedWith
Indicates a marital or spousal relationship or close association between two entities.
-
E.
roleDuringSpouseTenure
Indicates that a person held a particular role or position specifically during the period when their spouse was in office or serving in a defined tenure.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c862f481908d1faf6ed57774f1 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:39 p.m.