Triple
T36772186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Redwood forests of the Santa Cruz Mountains |
E908507
|
entity |
| Predicate | treeHeightTypical |
P573
|
FINISHED |
| Object | over 60 meters in mature stands |
—
|
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: over 60 meters in mature stands | Statement: [Redwood forests of the Santa Cruz Mountains, treeHeightTypical, over 60 meters in mature stands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treeHeightTypical Context triple: [Redwood forests of the Santa Cruz Mountains, treeHeightTypical, over 60 meters in mature stands]
-
A.
typicalHeight
chosen
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
plantHeight
Indicates the measured vertical size or growth extent of a plant from its base to its top.
-
C.
propertyType_height
Indicates a relationship where an entity’s height is specified as a property or attribute.
-
D.
heightAboveGround
Indicates the vertical distance of an entity measured from the ground surface directly beneath it.
-
E.
typicalTrellising
Indicates the standard or commonly used method of supporting and training plants (such as vines or crops) on a trellis structure.
- 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_69f76e786ba481909cdcf6cf6b39dd32 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.