Triple
T28495918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paleocene |
E721105
|
entity |
| Predicate | terrestrialFlora |
P953
|
FINISHED |
| Object | broadleaf evergreen forests at high latitudes |
—
|
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: broadleaf evergreen forests at high latitudes | Statement: [Paleocene, terrestrialFlora, broadleaf evergreen forests at high latitudes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terrestrialFlora Context triple: [Paleocene, terrestrialFlora, broadleaf evergreen forests at high latitudes]
-
A.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
B.
isLandPlant
Indicates that an entity is a plant that primarily lives and grows on land rather than in aquatic environments.
-
C.
associatedFlora
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.
-
D.
plantType
Indicates the specific kind or category of plant that an entity is classified as.
-
E.
vegetationType
chosen
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
- 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_69f01a5afdac8190ac6e72d5c100bd58 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f64f3ed46c8190bf19437b134edcf7 |
completed | May 2, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 3:04 a.m.