Triple
T9621436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sári |
E232348
|
entity |
| Predicate | hasAccentPosition |
P89305
|
FINISHED |
| Object | first syllable |
—
|
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: first syllable | Statement: [Sári, hasAccentPosition, first syllable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccentPosition Context triple: [Sári, hasAccentPosition, first syllable]
-
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.
hasCliticPlacement
Indicates the specific positional relationship of a clitic element relative to its host word or phrase in a linguistic structure.
-
D.
usesToneMarks
Indicates that one entity applies or includes diacritical tone marks in the representation or transcription of another entity (such as text, language, or symbols).
-
E.
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.
- 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_69ca84867bb88190b4b57dd5a56d5691 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad3a8d88190b1414aa676d82f36 |
completed | April 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69ccd5aa1d2c8190a287bf1cf4a3037e |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:10 p.m.