Triple
T36618263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer (Pinuno) of the Order of Lakandula |
E903663
|
entity |
| Predicate | rankLanguageVariant |
P186081
|
FINISHED |
| Object | Pinuno |
—
|
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: Pinuno | Statement: [Officer (Pinuno) of the Order of Lakandula, rankLanguageVariant, Pinuno]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankLanguageVariant Context triple: [Officer (Pinuno) of the Order of Lakandula, rankLanguageVariant, Pinuno]
-
A.
labelLanguageVariant
Indicates that one label is a language-specific variant or localized form of another label.
-
B.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
languageVariants
Indicates that one language form is a variant or alternative version of another language.
-
D.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
E.
officialLanguageVariant
Indicates that one language variety is an officially recognized form or version of another language within a specific jurisdiction or context.
- 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_69f76e6960e4819092047756ceb9a17e |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c83f5960819089610ed39c839678 |
completed | May 3, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f7c477a4d481908f52e55b6688f60c |
completed | May 3, 2026, 9:56 p.m. |
| PDg | Predicate description generation | batch_69f7c776b4088190bef550c869da530d |
completed | May 3, 2026, 10:08 p.m. |
Created at: May 3, 2026, 4:11 p.m.