Triple
T33415611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bonnie Swanson |
E855705
|
entity |
| Predicate | spouseDisability |
P195320
|
FINISHED |
| Object | paraplegic |
—
|
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: paraplegic | Statement: [Bonnie Swanson, spouseDisability, paraplegic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseDisability Context triple: [Bonnie Swanson, spouseDisability, paraplegic]
-
A.
spouseInjuryContext
Indicates a context in which an injury is specifically related to, affects, or involves a person’s spouse.
-
B.
spouseDeath
Indicates that one person's spouse has died, marking the event of the spouse's death in relation to that person.
-
C.
spouseInWork
Indicates that two entities are spouses within the context of a particular work (such as a book, film, or series), rather than in real life.
-
D.
spouseRetirementContext
Indicates that the situation or information is specifically about the retirement status, plans, or circumstances of a person's spouse.
-
E.
spouseRecognition
Indicates that one entity formally acknowledges another entity as their spouse within a recognized relationship.
- 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_69f3496f04a08190804e56ac5098b8e4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fdbaa226708190b8ed96e93aad38de |
completed | May 8, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_69fdb58b07e48190837e00966de050d4 |
completed | May 8, 2026, 10:06 a.m. |
| PDg | Predicate description generation | batch_69fdbaa1313081908beea28a5597ae40 |
completed | May 8, 2026, 10:27 a.m. |
Created at: May 1, 2026, 1:36 a.m.