Triple
T27956086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongding Hakka |
E703552
|
entity |
| Predicate | hasDialectalOriginOf |
P187371
|
FINISHED |
| Object | Taiwanese Hakka speech |
—
|
NE NERFINISHED |
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: Taiwanese Hakka speech | Statement: [Yongding Hakka, hasDialectalOriginOf, Taiwanese Hakka speech]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectalOriginOf Context triple: [Yongding Hakka, hasDialectalOriginOf, Taiwanese Hakka speech]
-
A.
hasDialectalCounterpart
Indicates that one linguistic form has a corresponding equivalent or variant in another dialect.
-
B.
hasDialectalDifferenceWith
Indicates that two language varieties differ from each other in dialectal features such as pronunciation, vocabulary, or grammar.
-
C.
hasDialectContinuumWith
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
-
D.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
E.
hasDialectalFeaturesSharedWith
Indicates that two language varieties share specific dialectal features or characteristics in common.
- 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_69ef840c8b2c8190946ae9522774ba51 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb563a28d88190b28345c465c545f8 |
completed | May 6, 2026, 2:54 p.m. |
Created at: April 27, 2026, 7:28 p.m.