Triple
T30821030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coastal Douglas-fir zone |
E784919
|
entity |
| Predicate | hasAssociatedTreeSpecies |
P6706
|
FINISHED |
| Object |
Garry oak
Garry oak is a hardy, drought-tolerant deciduous oak tree native to western North America, particularly characteristic of dry coastal and lowland ecosystems.
|
E1934483
|
NE FINISHED |
How this triple was built (3 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: Garry oak | Statement: [Coastal Douglas-fir zone, hasAssociatedTreeSpecies, Garry oak]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Garry oak Triple: [Coastal Douglas-fir zone, hasAssociatedTreeSpecies, Garry oak]
Generated description
Garry oak is a hardy, drought-tolerant deciduous oak tree native to western North America, particularly characteristic of dry coastal and lowland ecosystems.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedTreeSpecies Context triple: [Coastal Douglas-fir zone, hasAssociatedTreeSpecies, Garry oak]
-
A.
hasForestAssociation
Indicates an ecological or contextual relationship in which an entity is associated with, influenced by, or characteristically occurs in forest environments.
-
B.
hasTrees
Indicates that something possesses or contains one or more trees.
-
C.
hasForestType
Indicates that an area or location is characterized by a specific type or classification of forest.
-
D.
hasTree
chosen
Indicates that one entity possesses, contains, or is associated with a tree.
-
E.
hasScientificNameOfDominantTree
Indicates the scientific (Latin) name of the tree species that is dominant in a given area or context.
- F. None of above.
Provenance (6 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_69f224b6642481909e8d701de2cd1a53 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a28bbe77368819093b2b9832db29d64 |
completed | June 10, 2026, 1:20 a.m. |
| NEDg | Description generation | batch_6a28bcbbade88190a0782743d0033602 |
completed | June 10, 2026, 1:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28c0d7003881909b928df3a07d09ea |
completed | June 10, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
Created at: April 29, 2026, 8:44 p.m.