Triple
T11858735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wizard |
E282105
|
entity |
| Predicate | hasFameReason |
P52554
|
FINISHED |
| Object | defensive excellence |
—
|
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: defensive excellence | Statement: [The Wizard, hasFameReason, defensive excellence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFameReason Context triple: [The Wizard, hasFameReason, defensive excellence]
-
A.
fameFor
chosen
Indicates that one entity is widely known or recognized specifically because of, or in connection with, another entity.
-
B.
fameStatus
Indicates the level or state of public recognition or renown associated with an entity.
-
C.
hasPopularityReason
Indicates that there is a specific reason or factor explaining why something is popular.
-
D.
claimToFame
Indicates the notable achievement, characteristic, or association for which an entity is best known.
-
E.
helpedPropelToMainstreamFame
Indicates that one entity significantly contributed to another entity’s rise to widespread public recognition or mainstream popularity.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69a099c8190a674db64c50eca5a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.