Triple
T33644706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resuk language |
E861926
|
entity |
| Predicate | visibilityInLinguistics |
P36632
|
FINISHED |
| Object | low |
—
|
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: low | Statement: [Resuk language, visibilityInLinguistics, low]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: visibilityInLinguistics Context triple: [Resuk language, visibilityInLinguistics, low]
-
A.
visibilityInFiction
Indicates how prominently or frequently an entity appears or is portrayed within a fictional work or body of fiction.
-
B.
linguisticSignificance
chosen
Indicates the degree to which something is important, influential, or meaningful within a particular language or linguistic system.
-
C.
linguisticScope
Indicates the range or domain within language (such as a phrase, clause, or discourse segment) over which a particular linguistic element, feature, or operation has effect.
-
D.
languageModality
Indicates the mode or form in which a language is expressed or perceived (e.g., spoken, signed, written, or tactile).
-
E.
linguisticStudies
Indicates that an entity engages in or is associated with the academic study or analysis of language and its structure.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.