Triple
T15358726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Mario 3D Land |
E367231
|
entity |
| Predicate | hasMainWorldsCount |
P117199
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Super Mario 3D Land, hasMainWorldsCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainWorldsCount Context triple: [Super Mario 3D Land, hasMainWorldsCount, 8]
-
A.
hasWorldCount
chosen
Indicates that an entity is associated with a specific number of worlds.
-
B.
hasWorldNumber
Indicates that an entity is associated with a specific world identified by a particular number.
-
C.
hasWorld
Indicates that an entity possesses, is associated with, or encompasses a particular world or global context.
-
D.
hasWorldStructure
Indicates that an entity possesses or is characterized by a particular overall world-level organization, framework, or structural configuration.
-
E.
hasNumberOfCountries
Indicates the relationship that specifies how many countries are associated with or contained within a given entity.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2d4934819097fc63603964217c |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:18 a.m.