Triple
T4814698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Upsilon |
E107159
|
entity |
| Predicate | representsSoundHistorically |
P58360
|
FINISHED |
| Object | close back rounded vowel /u/ |
—
|
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: close back rounded vowel /u/ | Statement: [Upsilon, representsSoundHistorically, close back rounded vowel /u/]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsSoundHistorically Context triple: [Upsilon, representsSoundHistorically, close back rounded vowel /u/]
-
A.
historicalSoundValue
chosen
Indicates that an entity has a sound-related value or property that is specific to a past or historically documented state or period.
-
B.
representsSoundInModernHebrew
Indicates that one entity serves as the modern Hebrew sound representation or phonetic realization of another entity.
-
C.
historicallyRepresented
Indicates that one entity served as a representation, symbol, or stand-in for another entity during a specific historical period or context.
-
D.
historicallySpoke
Indicates that an entity used a particular language as a spoken language during some period in the past.
-
E.
depictsSound
Indicates that one entity visually represents or portrays the sound produced by another entity.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1dfa3481909d240d50ed0ee38c |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.