Triple
T23900082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yola language of County Wexford |
E601016
|
entity |
| Predicate | hasSampleTexts |
P102207
|
FINISHED |
| Object | songs and verses recorded in the 19th century |
—
|
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: songs and verses recorded in the 19th century | Statement: [Yola language of County Wexford, hasSampleTexts, songs and verses recorded in the 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSampleTexts Context triple: [Yola language of County Wexford, hasSampleTexts, songs and verses recorded in the 19th century]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasTextualCorpus
Indicates that an entity is associated with or possesses a collection of written or textual materials.
-
C.
hasRecordedTexts
chosen
Indicates that there exist written or otherwise recorded textual materials documenting or produced by the subject entity.
-
D.
containsTextsFor
Indicates that one entity holds or includes text content intended for use by another entity.
-
E.
hasTextFrom
Indicates that one entity contains, is derived from, or directly uses the textual content originating from another entity.
- 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_69e295364a488190bcac702e9bb7f764 |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdddca088190b6c26df984a143ad |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:26 p.m.