Triple
T24056831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paranthropus boisei |
E595828
|
entity |
| Predicate | laterGenusAssignment |
P33921
|
FINISHED |
| Object | Australopithecus |
—
|
NE NERFINISHED |
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: Australopithecus | Statement: [Paranthropus boisei, laterGenusAssignment, Australopithecus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterGenusAssignment Context triple: [Paranthropus boisei, laterGenusAssignment, Australopithecus]
-
A.
namedAfterTypeGenus
Indicates that an entity (such as a taxonomic group) is named after its type genus.
-
B.
previousGenus
chosen
Indicates that one genus was previously used as the taxonomic genus for an organism before being reclassified to another genus.
-
C.
laterSpecies
Indicates that one species appears or evolves later in time relative to another species.
-
D.
exampleGenus
Indicates that one entity is an example or instance illustrating the genus or general category represented by the other entity.
-
E.
hasGenus
Indicates that one entity belongs to, or is classified under, the biological genus represented by the other entity.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1da50d6108190a36bffaa475c8b93 |
completed | April 29, 2026, 10:15 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:34 p.m.