Triple
T2675693
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aizoaceae |
E56453
|
entity |
| Predicate | approximateNumberOfGenera |
P12302
|
FINISHED |
| Object | about 120 |
—
|
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: about 120 | Statement: [Aizoaceae, approximateNumberOfGenera, about 120]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfGenera Context triple: [Aizoaceae, approximateNumberOfGenera, about 120]
-
A.
numberOfGenera
chosen
Indicates the total count of genera associated with or contained within a given entity.
-
B.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
C.
notableGenus
Indicates that one entity is a genus that is especially prominent, well-known, or significant in relation to the other entity.
-
D.
approximateNumberOfGalaxies
Indicates an estimated or roughly calculated count of galaxies associated with a given subject.
-
E.
genusIncludes
Indicates that a particular genus contains or encompasses the specified subordinate taxonomic entities (such as species or subspecies).
- 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.