Triple
T38584841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Black Morass |
E932322
|
entity |
| Predicate | geographicalTheme |
P52634
|
FINISHED |
| Object | swamp |
—
|
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: swamp | Statement: [The Black Morass, geographicalTheme, swamp]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicalTheme Context triple: [The Black Morass, geographicalTheme, swamp]
-
A.
geographicalNature
chosen
Indicates the natural geographic characteristics or physical landscape type associated with a place or region.
-
B.
geographicalPractice
Indicates a relationship where an entity engages in or is associated with a practice, activity, or method that is specific to or characteristic of a particular geographic area or location.
-
C.
geographyBehavior
Indicates how an entity behaves, functions, or interacts in relation to its geographic context or location.
-
D.
inWorldGeography
Indicates that something is located within or belongs to the physical geography of the world (such as a region, landscape, or geographic setting).
-
E.
geographicalReality
Indicates that something pertains to, reflects, or is constrained by actual physical geography or spatial conditions in the real world.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
Created at: May 3, 2026, 4:32 p.m.