Triple
T3410762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turn 2 Foundation |
E71886
|
entity |
| Predicate | notableFounderPosition |
P5394
|
FINISHED |
| Object | shortstop |
—
|
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: shortstop | Statement: [Turn 2 Foundation, notableFounderPosition, shortstop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableFounderPosition Context triple: [Turn 2 Foundation, notableFounderPosition, shortstop]
-
A.
hasNotableFounder
Indicates that an entity was founded or established by a person or organization considered especially significant or noteworthy.
-
B.
founderKnownFor
Indicates that a founder is particularly recognized or notable for a specific work, achievement, product, or contribution.
-
C.
notableCEO
Indicates that the subject is a chief executive officer who is widely recognized or distinguished in a notable way.
-
D.
foundingRole
chosen
Indicates the specific role or capacity an entity held in the founding or establishment of another entity.
-
E.
notableHolderOccupation
Indicates that a person notably associated with an entity (e.g., an award, office, or title) held a particular occupation or professional role.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb9094b2881909262e58a470ed9d0 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfa73ac8190a163f93e88d217f8 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.