Triple
T14246007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Tagimoucia |
E353134
|
entity |
| Predicate | hasAssociatedFlora |
P83264
|
FINISHED |
| Object | Tagimoucia flower |
—
|
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: Tagimoucia flower | Statement: [Lake Tagimoucia, hasAssociatedFlora, Tagimoucia flower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedFlora Context triple: [Lake Tagimoucia, hasAssociatedFlora, Tagimoucia flower]
-
A.
associatedFlora
chosen
Indicates a relationship where specific plants or vegetation are characteristically linked to, occur with, or are commonly found in association with a given entity or environment.
-
B.
hasFloraGroup
Indicates that an entity is associated with, contains, or is characterized by a particular group or category of plant life.
-
C.
containsPlantsWith
Indicates that one entity includes or holds within it one or more plant entities.
-
D.
hasBotanicalResource
Indicates that an entity possesses, contains, or is associated with a plant-based resource (such as plants, plant parts, or botanical materials) used for some purpose.
-
E.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de629464f88190817b190731bab156 |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.