Triple
T7124546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dimasa language |
E166026
|
entity |
| Predicate | hasNumberMarking |
P35097
|
FINISHED |
| Object | plural suffixes |
—
|
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: plural suffixes | Statement: [Dimasa language, hasNumberMarking, plural suffixes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberMarking Context triple: [Dimasa language, hasNumberMarking, plural suffixes]
-
A.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
-
B.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
C.
hasBandNumber
Indicates that an entity is associated with a specific band identification number.
-
D.
hasLockNumber
Indicates that an entity is associated with a specific lock identified by a number.
-
E.
hasNumberDistinction
chosen
Indicates that a language or system grammatically distinguishes between different numbers (such as singular, plural, dual, etc.) in its expressions.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e64c0f688190a9b7482d86c2f033 |
completed | March 27, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c7289881909f3b533c384f9ed4 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:44 p.m.