Triple
T24745520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stretch |
E618684
|
entity |
| Predicate | personNicknamedOccupation |
P12884
|
FINISHED |
| Object | professional baseball player |
—
|
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: professional baseball player | Statement: [Stretch, personNicknamedOccupation, professional baseball player]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personNicknamedOccupation Context triple: [Stretch, personNicknamedOccupation, professional baseball player]
-
A.
namedPersonOccupation
chosen
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
B.
notableNickname
Indicates that one entity is a well-known or widely recognized nickname or moniker for another entity.
-
C.
nicknamedFor
Indicates that one entity serves as the source, inspiration, or reason for another entity’s nickname.
-
D.
isOfficialNicknameOf
Indicates that one name is the formally recognized nickname or informal moniker used to refer to another entity.
-
E.
namesakeOccupation
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a25ab88190a72db43043c1f6ff |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 4:21 a.m.