Triple
T27454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas |
E548
|
entity |
| Predicate | hasDiverseLandscape |
P1895
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Texas, hasDiverseLandscape, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiverseLandscape Context triple: [Texas, hasDiverseLandscape, true]
-
A.
hasNaturalFeature
Indicates that one entity possesses, contains, or is characterized by a particular natural feature (such as a mountain, river, forest, or coastline).
-
B.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
C.
hasMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a specific mountain range.
-
D.
hasMajorMountainRange
Indicates that one entity possesses, contains, or is geographically associated with a principal or significant mountain range.
-
E.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a247798a348190bb943d38300ae3ef |
completed | Feb. 28, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69a24658749881909117b007ec3d8633 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a24778b73c81908e9f2eb8cdbcef73 |
completed | Feb. 28, 2026, 1:40 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.