Triple
T35067672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trouble in Lumpy Space |
E1011773
|
entity |
| Predicate | settingDimension |
P193381
|
FINISHED |
| Object | Lumpy Space |
—
|
NE NERFINISHED |
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: Lumpy Space | Statement: [Trouble in Lumpy Space, settingDimension, Lumpy Space]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingDimension Context triple: [Trouble in Lumpy Space, settingDimension, Lumpy Space]
-
A.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
B.
graphicsDimension
Indicates a relationship where an entity has or is associated with a specific graphical size or dimensional properties.
-
C.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
D.
externalDimension
Indicates that an entity has a measurable size or extent along one or more outer spatial dimensions (such as length, width, or height).
-
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_69f76dd193108190af2528186f25b72a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69fd4445f8c08190bb2dc27e0971c55d |
completed | May 8, 2026, 2:02 a.m. |
Created at: May 3, 2026, 4:01 p.m.