Triple
T4215981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scutia |
E94215
|
entity |
| Predicate | isTaxonAuthoritativeLanguage |
P54802
|
FINISHED |
| Object | Latin name |
—
|
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: Latin name | Statement: [Scutia, isTaxonAuthoritativeLanguage, Latin name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTaxonAuthoritativeLanguage Context triple: [Scutia, isTaxonAuthoritativeLanguage, Latin name]
-
A.
taxonomicAuthority
Indicates the entity that formally described, named, or classified another entity in a taxonomic context.
-
B.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
C.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
D.
isUNOfficialLanguage
Indicates that a language holds official status within the United Nations.
-
E.
hasOfficialNameInLatin
Indicates that an entity has an official or formally recognized name expressed in the Latin language.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e04ef1c81908bb34ae1cbfab1e6 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:04 p.m.