Triple
T2079309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Garnett |
E45200
|
entity |
| Predicate | allDefensiveSelections |
P20783
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Kevin Garnett, allDefensiveSelections, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allDefensiveSelections Context triple: [Kevin Garnett, allDefensiveSelections, 12]
-
A.
AllDefensiveSelection
chosen
Indicates that an entity has been chosen for inclusion on an all-defensive team or recognized for outstanding defensive performance within a competitive context.
-
B.
defensivePlan
Indicates a relationship where an entity formulates or adopts a strategy specifically intended to protect against threats, attacks, or other adverse actions.
-
C.
defensiveRole
Indicates that an entity serves a protective or guarding function in relation to another entity or context.
-
D.
defensiveTactics
Indicates the use or implementation of strategies, maneuvers, or methods intended to protect, guard, or defend against threats or attacks.
-
E.
defensiveStructure
Indicates a relationship where one entity functions as a structure built or used to protect, defend, or fortify another entity or area.
- 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_69a8891869c88190a02643e3bb746f59 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba3307308190ab329fe3192b2e0f |
completed | March 7, 2026, 5:40 a.m. |
| PD | Predicate disambiguation | batch_69abb7b0edac8190a58eabee55f73deb |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:41 p.m.