Triple
T13082207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Insecta |
E310235
|
entity |
| Predicate | estimatedDescribedSpecies |
P6211
|
FINISHED |
| Object | over 1 million |
—
|
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 million | Statement: [Insecta, estimatedDescribedSpecies, over 1 million]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: estimatedDescribedSpecies Context triple: [Insecta, estimatedDescribedSpecies, over 1 million]
-
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.
hasWildPopulationOf
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
-
D.
numberOfSurvivingSpecimens
Indicates the count of individual specimens that remain alive or intact after a particular event, period, or condition.
-
E.
mostNumerousSubspeciesOf
Indicates that one subspecies has the largest population size compared to all other subspecies within the same parent species.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d9811add9881908a92186dab5b6d48 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:01 p.m.