Triple
T8834578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalinago language |
E210233
|
entity |
| Predicate | hasGenderlects |
P12026
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Kalinago language, hasGenderlects, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderlects Context triple: [Kalinago language, hasGenderlects, yes]
-
A.
hasGenderDistinction
chosen
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
B.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
C.
hasGenderVariant
Indicates that one entity is a gender-specific form or variant of another entity.
-
D.
hasNameGenderUsage
Indicates that a particular name is used with a specific gender or set of genders in a given context.
-
E.
hasColloquialVariety
Indicates that one linguistic form, expression, or variety is an informal, colloquial counterpart or version of another.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60686cac8190b3138db40b6fe058 |
completed | April 1, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:47 p.m.