Triple
T26017997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tim Wakefield |
E647073
|
entity |
| Predicate | spentMostOfCareerWith |
P80842
|
FINISHED |
| Object | Boston Red Sox |
—
|
NE NERFINISHED |
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: Boston Red Sox | Statement: [Tim Wakefield, spentMostOfCareerWith, Boston Red Sox]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spentMostOfCareerWith Context triple: [Tim Wakefield, spentMostOfCareerWith, Boston Red Sox]
-
A.
spentMostOfCareerIn
chosen
Indicates that an individual devoted the majority of their professional working life to being in or associated with a particular place, organization, or context.
-
B.
spentEntireCareerWith
Indicates that an individual has worked exclusively for a single organization or team for the full duration of their professional career.
-
C.
leagueWorkedFor
Indicates that an individual has been employed by or has worked for a particular sports league.
-
D.
workedPrimarilyIn
Indicates that an entity carried out the majority of its work, activity, or career within a particular field, location, or context.
-
E.
spentMostOfLifeIn
Indicates that an entity resided or was primarily based in a particular place for the majority of its lifetime.
- 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_69e77e8aa65881909ca58918f29ab2a0 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f605bab4e48190b6a9316a2b652b1b |
completed | May 2, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69f4a10728e08190bc0b96c558740f51 |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 9:03 a.m.