Triple
T34186086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tonto Creek watershed |
E876963
|
entity |
| Predicate | containsLandCoverType |
P2022
|
FINISHED |
| Object | montane forest |
—
|
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: montane forest | Statement: [Tonto Creek watershed, containsLandCoverType, montane forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLandCoverType Context triple: [Tonto Creek watershed, containsLandCoverType, montane forest]
-
A.
hasLandCoverage
chosen
Indicates that a specified area or region is covered or occupied by a particular type of land surface or land use.
-
B.
hasLandClassification
Indicates the designated land-use or land-cover category assigned to a particular area or parcel.
-
C.
isInLandAreaType
Indicates that one entity is located within, or belongs to, a specified type of land area (such as urban, rural, coastal, or agricultural).
-
D.
vegetationCoverage
Indicates the extent or proportion of an area that is covered by vegetation.
-
E.
forestCoverCharacteristic
Indicates a relationship where a forested area possesses a specific attribute or quality related to its tree or vegetation cover.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a005d878aec81908e1177914a8fb610 |
completed | May 10, 2026, 10:27 a.m. |
| PD | Predicate disambiguation | batch_6a005c382f8881908ff33ebb7f88c430 |
completed | May 10, 2026, 10:21 a.m. |
Created at: May 1, 2026, 1:55 a.m.