Triple
T21810199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Microbiotheria |
E538450
|
entity |
| Predicate | bodySizeOfRepresentativeSpecies |
P62520
|
FINISHED |
| Object | mouse-sized |
—
|
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: mouse-sized | Statement: [Microbiotheria, bodySizeOfRepresentativeSpecies, mouse-sized]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodySizeOfRepresentativeSpecies Context triple: [Microbiotheria, bodySizeOfRepresentativeSpecies, mouse-sized]
-
A.
hasLargeSpecies
Indicates that an entity possesses or includes at least one species that is considered large in size.
-
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.
maximumMaleBodyLength
Indicates the greatest recorded body length measured for male individuals of a given entity or species.
-
D.
physicalCharacteristics
chosen
Indicates that one entity has or describes the bodily or material attributes, features, or appearance of another entity.
-
E.
maximumFemaleBodyLength
Indicates the greatest recorded length of the body for female individuals of a given entity or group.
- 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_69e0c473f0f8819086c9d1b4a143bd67 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f07cc5fd948190a404a050404db975 |
completed | April 28, 2026, 9:24 a.m. |
| PD | Predicate disambiguation | batch_69e6be815a108190be81d7c987d0c0d6 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:53 p.m.