Triple
T2396310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cyprinodontiformes |
E47658
|
entity |
| Predicate | containsModelOrganisms |
P37909
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cyprinodontiformes, containsModelOrganisms, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsModelOrganisms Context triple: [Cyprinodontiformes, containsModelOrganisms, true]
-
A.
isModelOrganism
Indicates that one organism is used as a representative experimental system for studying biological processes relevant to other organisms.
-
B.
notableModelOrganism
Indicates that an organism is widely recognized and frequently used as a standard or reference model for scientific research or experimentation.
-
C.
includesSpecies
Indicates that one entity contains or encompasses one or more species as part of its composition or scope.
-
D.
hasOrganSystem
Indicates that an entity possesses or is associated with a particular organ system as part of its biological structure or function.
-
E.
someSpeciesAre
Indicates that at least one member of a specified group or category belongs to, or can be classified as, a particular 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc8c4a8bc819086892a75caac0207 |
completed | March 7, 2026, 6:42 a.m. |
| PD | Predicate disambiguation | batch_69abc5a3825c81909ec6111dfc165453 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc664317c8190a6bb5a5065c21bde |
completed | March 7, 2026, 6:32 a.m. |
Created at: March 4, 2026, 7:57 p.m.