Triple
T24792840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coy |
E620295
|
entity |
| Predicate | hasOrthographicCase |
P12752
|
FINISHED |
| Object | capitalized as a proper noun |
—
|
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: capitalized as a proper noun | Statement: [Coy, hasOrthographicCase, capitalized as a proper noun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOrthographicCase Context triple: [Coy, hasOrthographicCase, capitalized as a proper noun]
-
A.
hasOrthographicConvention
Indicates that there is a specific writing or spelling convention that governs how something is represented in written form.
-
B.
hasOrthographicReform
Indicates that an entity has undergone or is associated with a change or standardization in its writing system or spelling conventions.
-
C.
hasOrthographicPreference
Indicates that one entity prefers or selects a particular written or spelling form of another entity.
-
D.
orthographicProperty
chosen
Indicates a relationship where a specific written or spelling-related characteristic is attributed to or associated with an entity.
-
E.
hasOrthographyStatus
Indicates the orthographic status or condition of how something is written or spelled, such as its conformity to a particular writing system or standard.
- 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 4:47 a.m.