Triple
T2675694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aizoaceae |
E56453
|
entity |
| Predicate | approximateNumberOfSpecies |
P6211
|
FINISHED |
| Object | over 1800 |
—
|
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 1800 | Statement: [Aizoaceae, approximateNumberOfSpecies, over 1800]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfSpecies Context triple: [Aizoaceae, approximateNumberOfSpecies, over 1800]
-
A.
numberOfSpecies
chosen
Indicates the count of distinct species associated with a given entity or context.
-
B.
numberOfGenera
Indicates the total count of genera associated with or contained within a given entity.
-
C.
hasWildPopulationOf
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
-
D.
someSpeciesAre
Indicates that at least one member of a specified group or category belongs to, or can be classified as, a particular species.
-
E.
approximateStellarCount
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9b3530c819093942cc985f814ef |
completed | March 7, 2026, 7:54 a.m. |
| PD | Predicate disambiguation | batch_69abd8190ad481908f3e14ac84d0940a |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.