Triple
T4010006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seán |
E90618
|
entity |
| Predicate | accentMarkIndicates |
P18659
|
FINISHED |
| Object | long vowel sound in á |
—
|
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: long vowel sound in á | Statement: [Seán, accentMarkIndicates, long vowel sound in á]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accentMarkIndicates Context triple: [Seán, accentMarkIndicates, long vowel sound in á]
-
A.
hasAccent
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
B.
accentedFormOf
Indicates that one linguistic form is an accented or diacritically marked variant of another, more basic form.
-
C.
hasCaseMarking
Indicates that a linguistic element (such as a noun or pronoun) bears a specific grammatical case marking that signals its syntactic or semantic role in a clause.
-
D.
diacriticType
chosen
Indicates the specific kind or category of diacritic mark associated with a character or symbol.
-
E.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.