Triple
T8467057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glires |
E200189
|
entity |
| Predicate | containsMostMammalSpecies |
P83443
|
FINISHED |
| Object | through Rodentia |
—
|
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: through Rodentia | Statement: [Glires, containsMostMammalSpecies, through Rodentia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsMostMammalSpecies Context triple: [Glires, containsMostMammalSpecies, through Rodentia]
-
A.
hasMammalSpecies
Indicates that one entity includes, contains, or is associated with a particular mammal species as part of its composition, population, or classification.
-
B.
hasLargestSpecies
Indicates that one entity possesses, contains, or is associated with the species that is largest in size or extent within a given group or context.
-
C.
hasEndemicSpecies
Indicates that a place or region contains species that are native to and found only within that specific geographic area.
-
D.
numberOfSpecies
Indicates the count of distinct species associated with a given entity or context.
-
E.
hasWildPopulationOf
Indicates that a location or area contains a naturally occurring, non-captive population of the specified species.
- F. None of above. chosen
Provenance (4 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4d2eb648190b606411eb6a8f7ea |
completed | March 31, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69cbd10072cc819084be1ed9ac7ebe9d |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe30c2d088190b4cb89adb4e88273 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:11 p.m.