Triple
T13219427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sky Land |
E314709
|
entity |
| Predicate | belongsToGameWorldSet |
P85633
|
FINISHED |
| Object | eight main worlds of Super Mario Bros. 3 |
—
|
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: eight main worlds of Super Mario Bros. 3 | Statement: [Sky Land, belongsToGameWorldSet, eight main worlds of Super Mario Bros. 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToGameWorldSet Context triple: [Sky Land, belongsToGameWorldSet, eight main worlds of Super Mario Bros. 3]
-
A.
associatedWithGame
Indicates that there is a relationship or connection between an entity and a particular game.
-
B.
associatedWithGameNumber
Indicates a relationship where something is linked or tied to a specific game identified by its number.
-
C.
hasWorldNumber
Indicates that an entity is associated with a specific world identified by a particular number.
-
D.
notableGameWorld
chosen
Indicates that a game’s world or setting is particularly significant, distinguished, or noteworthy in some meaningful way.
-
E.
partOfHeroicEquipmentSetOf
Indicates that an item is a component belonging to a specific heroic equipment set.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf581508190883033f0c961736a |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:18 p.m.