Triple
T2006446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coptic language |
E43596
|
entity |
| Predicate | hasNumberDistinction |
P35097
|
FINISHED |
| Object | singular and plural |
—
|
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: singular and plural | Statement: [Coptic language, hasNumberDistinction, singular and plural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberDistinction Context triple: [Coptic language, hasNumberDistinction, singular and plural]
-
A.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
-
B.
hasNumberCategory
Indicates that an entity is associated with a specific numerical classification or type.
-
C.
hasRegisterDistinction
Indicates that there is a meaningful difference in language register (e.g., formality or style) between the related linguistic forms or usages.
-
D.
hasOppositeNumberForm
Indicates that one entity is represented by a number form that is the opposite (e.g., additive vs. subtractive, positive vs. negative, or otherwise contrastive) of the number form used to represent the other entity.
-
E.
usesHarmonizedNumberingWith
Indicates that two entities apply the same standardized numbering scheme so their identifiers or codes are directly comparable or aligned.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8999e108190a07daa01452a5dab |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.