Triple
T20354211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shikahogh State Reserve |
E496098
|
entity |
| Predicate | floraSpeciesCount |
P6211
|
FINISHED |
| Object | over 1,000 plant species |
—
|
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 1,000 plant species | Statement: [Shikahogh State Reserve, floraSpeciesCount, over 1,000 plant species]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floraSpeciesCount Context triple: [Shikahogh State Reserve, floraSpeciesCount, over 1,000 plant species]
-
A.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
B.
speciesNumber
Indicates the numerical identifier or count associated with a particular species in a given context.
-
C.
studiedFloraOf
Indicates that a subject conducted research or examination on the plant life (flora) of a specified object or region.
-
D.
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.
-
E.
numberOfGenera
Indicates the total count of genera associated with or contained within a given entity.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67852ca9881908a5af18005639859 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:25 a.m.