Triple
T11660018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woodland Mansion |
E277096
|
entity |
| Predicate | generationDimension |
P100830
|
FINISHED |
| Object | Overworld |
—
|
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: Overworld | Statement: [Woodland Mansion, generationDimension, Overworld]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generationDimension Context triple: [Woodland Mansion, generationDimension, Overworld]
-
A.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
B.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
C.
generationCount
Indicates the number of times a process, entity, or version has been created, iterated, or regenerated within a sequence or lifecycle.
-
D.
dimension
Indicates that one entity specifies a measurable extent or size attribute (such as length, width, height, or similar quantitative property) of another entity.
-
E.
dimensionOfCurrent
Indicates the dimensional property (such as magnitude or units) associated with the current in a given context.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d19c788190826d849a6ffedc72 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d88a73f9ac819095662042804bf40a |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:39 p.m.