Triple
T5666452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bleek and Lloyd Collection |
E124868
|
entity |
| Predicate | languageContent |
P31857
|
FINISHED |
| Object | |Xam language |
—
|
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: |Xam language | Statement: [Bleek and Lloyd Collection, languageContent, |Xam language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageContent Context triple: [Bleek and Lloyd Collection, languageContent, |Xam language]
-
A.
contentLanguage
chosen
Indicates the language in which the content is expressed or intended to be understood.
-
B.
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.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
E.
languageView
Indicates a relationship where one entity views, interprets, or presents another entity through the lens of a particular language or linguistic perspective.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.