Triple
T30521273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troy Bayliss |
E776698
|
entity |
| Predicate | laterCameOutOfRetirement |
P17858
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Troy Bayliss, laterCameOutOfRetirement, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterCameOutOfRetirement Context triple: [Troy Bayliss, laterCameOutOfRetirement, 2015]
-
A.
returnedFromRetirement
chosen
Indicates that an entity has resumed an activity, role, or position after having previously retired from it.
-
B.
retiredFromSidelines
Indicates that an entity has ended its role or involvement from a previously inactive, observing, or non-participatory position in a given context.
-
C.
retiredAfter
Indicates that one entity stopped working or ended its professional career at a later time than another entity.
-
D.
retiredFrom
Indicates that an entity has permanently stopped working for or being active in a specified organization, role, or activity.
-
E.
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.
- 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_69f2249b23c4819087fa85496d92f43f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fef8c3f2388190b995ec173512945a |
completed | May 9, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69fef65975608190960b78d27e806d4f |
completed | May 9, 2026, 8:54 a.m. |
Created at: April 29, 2026, 8:17 p.m.