Triple
T2934699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Mario Bros. 3 |
E79236
|
entity |
| Predicate | notableWorld |
P44031
|
FINISHED |
| Object | Grass Land |
—
|
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: Grass Land | Statement: [Super Mario Bros. 3, notableWorld, Grass Land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableWorld Context triple: [Super Mario Bros. 3, notableWorld, Grass Land]
-
A.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
B.
notableCountry
Indicates that a country holds particular significance or prominence in relation to the subject entity.
-
C.
notableInRegion
Indicates that an entity is recognized as notable, prominent, or significant within a specified geographic region.
-
D.
notablePlace
Indicates that a place is especially significant, famous, or noteworthy in relation to the subject.
-
E.
notableDuring
Indicates that something was especially prominent, active, or significant during a particular time period or event.
- F. None of above. chosen
Provenance (4 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_69ad8b0fbab081908f6a61567c045d8d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad983c84688190aa7ed5b8091fb140 |
completed | March 8, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69ad96088fb481909976b436c2b729d9 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad97f520208190a4dc43372004555f |
completed | March 8, 2026, 3:38 p.m. |
Created at: March 8, 2026, 2:56 p.m.