Triple
T18694592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thaleia |
E457084
|
entity |
| Predicate | hasAccentPattern |
P114080
|
FINISHED |
| Object | accent on first syllable in Ancient Greek |
—
|
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: accent on first syllable in Ancient Greek | Statement: [Thaleia, hasAccentPattern, accent on first syllable in Ancient Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccentPattern Context triple: [Thaleia, hasAccentPattern, accent on first syllable in Ancient Greek]
-
A.
hasAccent
Indicates that an entity speaks with or possesses a particular accent or distinctive pronunciation style.
-
B.
hasAccentPosition
Indicates the position within a word or phrase where the primary accent or stress is placed.
-
C.
hasAccentSystem
chosen
Indicates that an entity employs or is characterized by a particular system or pattern of accents (e.g., in language, music, or typography).
-
D.
hasTitleAccentMarks
Indicates that the title contains one or more accented characters or diacritical marks.
-
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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e66a188190801fd95f9be26042 |
completed | April 19, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69e478de85088190ba5f005f1d39f587 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.