Triple
T36999188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | three-spined stickleback |
E915304
|
entity |
| Predicate | modelForProcess |
P2006
|
FINISHED |
| Object | speciation |
—
|
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: speciation | Statement: [three-spined stickleback, modelForProcess, speciation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelForProcess Context triple: [three-spined stickleback, modelForProcess, speciation]
-
A.
modelIn
Indicates that one entity serves as a representation or simulation of another entity.
-
B.
model
chosen
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
C.
producedModel
Indicates that one entity created, manufactured, or generated the other entity as a model or product.
-
D.
modelClass
Indicates that one entity serves as the class, type, or template definition for another entity that is an instance or implementation of it.
-
E.
planningModelFor
Indicates that one entity serves as a planning model used to guide, simulate, or structure the planning activities related to another 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.