Triple
T26868512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Machaeropterus |
E676539
|
entity |
| Predicate | taxonAuthorCountry |
P6689
|
FINISHED |
| Object | France |
—
|
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: France | Statement: [Machaeropterus, taxonAuthorCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: taxonAuthorCountry Context triple: [Machaeropterus, taxonAuthorCountry, France]
-
A.
taxonomicAuthority
Indicates the entity that formally described, named, or classified another entity in a taxonomic context.
-
B.
countryOfEponym
Indicates that the related entity is named after something (an eponym) originating from or associated with a particular country.
-
C.
authorNationality
chosen
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
D.
countryOfNotableWork
Indicates the country with which a notable work is primarily associated, such as where it was created, set, or gained its significance.
-
E.
creatorCountryOfBirth
Indicates the country where the creator of an entity was born.
- 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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69f61e99f138819097659bf61b6b35c2 |
completed | May 2, 2026, 3:56 p.m. |
| PD | Predicate disambiguation | batch_69f611ad2eb48190ac1ed0090f13f7a9 |
completed | May 2, 2026, 3:01 p.m. |
Created at: April 27, 2026, 5:30 a.m.