Triple
T4871426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knights Templar |
E109091
|
entity |
| Predicate | languageOfRule |
P51222
|
FINISHED |
| Object | Latin |
—
|
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 | Statement: [Knights Templar, languageOfRule, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfRule Context triple: [Knights Templar, languageOfRule, Latin]
-
A.
officialLanguageOfRules
chosen
Indicates that a specified language is the formally designated language used for the rules or regulations of a given entity or system.
-
B.
languageOfInterpretation
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
-
C.
languageCriterion
Indicates that a relationship or selection is based on whether something meets a specified language-related requirement or condition.
-
D.
governingLanguage
Indicates the language that holds official or authoritative status over a given entity, such as a region, organization, or document.
-
E.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c28e56081908ee411ac94c3769e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:27 p.m.