Triple
T35723490
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hardella |
E1032544
|
entity |
| Predicate | hasCommonNameSpecies |
P168444
|
FINISHED |
| Object | crown river turtle |
—
|
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: crown river turtle | Statement: [Hardella, hasCommonNameSpecies, crown river turtle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonNameSpecies Context triple: [Hardella, hasCommonNameSpecies, crown river turtle]
-
A.
includesSpeciesCommonName
Indicates that an entity contains or specifies the common (vernacular) name of a species.
-
B.
taxonCommonName
chosen
Indicates that a taxonomic entity is associated with a common (vernacular) name used in everyday language.
-
C.
hasCommonSpecies
Indicates that two entities share at least one species in common.
-
D.
nameIsCommonIn
Indicates that a given name is frequently used or widely occurring within a specified group, region, or context.
-
E.
commonNameOfNotableSpecies
Indicates that the subject is a commonly used vernacular or everyday name for a notable or well-known biological species.
- 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_69f76e102b5881909e5d63a30a5cecbe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:05 p.m.