Triple
T18885819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taxodium mucronatum |
E461952
|
entity |
| Predicate | Árbol del TuleCharacteristic |
P133674
|
FINISHED |
| Object | one of the stoutest tree trunks in the world |
—
|
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: one of the stoutest tree trunks in the world | Statement: [Taxodium mucronatum, Árbol del TuleCharacteristic, one of the stoutest tree trunks in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Árbol del TuleCharacteristic Context triple: [Taxodium mucronatum, Árbol del TuleCharacteristic, one of the stoutest tree trunks in the world]
-
A.
notableTreeSpecies
Indicates that the subject place or area is known for, or characterized by, the specified tree species.
-
B.
nationalTree
Indicates that a particular tree species is officially designated as the national tree of a country or region.
-
C.
市の木
Indicates the officially designated tree that represents a particular city.
-
D.
isGiantSequoiaOf
Indicates that one entity is a giant sequoia tree that belongs to, is located in, or is otherwise associated with another entity (such as a place or collection).
-
E.
الغطاء النباتي
Indicates the presence, extent, or characteristics of plant cover in a given 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c4760d808190b502c4ed1f24424c |
completed | April 20, 2026, 6:15 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e27e1481908a8da10b28f07875 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4afa745c081908da20a51ebc147b4 |
completed | April 19, 2026, 10:34 a.m. |
Created at: April 10, 2026, 11:57 a.m.