Triple
T20787310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crooked Tree |
E511672
|
entity |
| Predicate | hasNearbyEcosystemType |
P141543
|
FINISHED |
| Object | wetland |
—
|
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: wetland | Statement: [Crooked Tree, hasNearbyEcosystemType, wetland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyEcosystemType Context triple: [Crooked Tree, hasNearbyEcosystemType, wetland]
-
A.
hasNearbyHabitats
Indicates that one entity has other habitats located close to it in geographic or spatial terms.
-
B.
hasNearbyForestType
Indicates that one entity is located close to, or in the vicinity of, a forest of a specified type.
-
C.
hasNearbyLandscapeType
Indicates that one entity is located close to, or in the vicinity of, a particular type of landscape.
-
D.
hasNearbyWetlandRegion
Indicates that a given location or area is situated close to, or in the vicinity of, a wetland region.
-
E.
hasNearbySiteType
Indicates that one entity has another entity of a specified site type located in its close physical vicinity.
- 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_69e0b4cb83948190bd57bec21d78ed53 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c28d24708190bf3890a22d1ec4b7 |
completed | April 21, 2026, 12:19 a.m. |
| PD | Predicate disambiguation | batch_69e5c0575b1c81908d010223fcd1213e |
completed | April 20, 2026, 5:57 a.m. |
| PDg | Predicate description generation | batch_69e5c3cbe5788190b7ace43bfdac2ef6 |
completed | April 20, 2026, 6:12 a.m. |
Created at: April 16, 2026, 12:38 p.m.