Triple
T12174132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Stalteri |
E290045
|
entity |
| Predicate | afterRetirement |
P10023
|
FINISHED |
| Object | worked as a coach |
—
|
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: worked as a coach | Statement: [Paul Stalteri, afterRetirement, worked as a coach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afterRetirement Context triple: [Paul Stalteri, afterRetirement, worked as a coach]
-
A.
retired
Indicates that an entity has permanently stopped working in their former occupation or role, typically after reaching a certain age or service duration.
-
B.
roleAfterRetirement
chosen
Indicates the position, function, or status an entity assumes after it has retired from its previous role or activity.
-
C.
retiredTo
Indicates that an entity has permanently left active service or work and taken up residence or status in a particular place or role as their retirement destination.
-
D.
spentLaterLifeAt
Indicates that an individual resided, worked, or was primarily based at a particular place during the later period of their life.
-
E.
returnedFromRetirement
Indicates that an entity has resumed an activity, role, or position after having previously retired from it.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.