Triple
T27002170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upper Maguindanaon |
E680139
|
entity |
| Predicate | hasDialectRelationshipWith |
P78566
|
FINISHED |
| Object | Lower Maguindanaon |
—
|
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: Lower Maguindanaon | Statement: [Upper Maguindanaon, hasDialectRelationshipWith, Lower Maguindanaon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectRelationshipWith Context triple: [Upper Maguindanaon, hasDialectRelationshipWith, Lower Maguindanaon]
-
A.
hasDialectsIn
Indicates that a language or linguistic variety possesses distinct dialects that are used or found within a specified region or context.
-
B.
hasDialectCounterpart
Indicates that one linguistic form or expression has a corresponding equivalent in another dialect.
-
C.
hasDialectChainWith
Indicates that two language varieties are connected through a continuous sequence of mutually intelligible dialects forming a dialect chain.
-
D.
hasDialects
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
E.
relatedDialect
chosen
Indicates that one dialect has a recognized linguistic relationship or close affinity to another dialect.
- 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_69eeeb52908c8190bd246244686aa455 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 27, 2026, 6:58 a.m.