Triple
T720240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balinese script |
E14599
|
entity |
| Predicate | hasNuktaLikeSigns |
P18518
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Balinese script, hasNuktaLikeSigns, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNuktaLikeSigns Context triple: [Balinese script, hasNuktaLikeSigns, true]
-
A.
hasViramaSign
Indicates that a character or script element is associated with, or takes, a virama sign used to suppress the inherent vowel in abugida writing systems.
-
B.
hasConsonantSigns
Indicates that one entity possesses or includes consonant sign characters as part of its representation or structure.
-
C.
hasNasalVowels
Indicates that the subject language or phonological system includes vowels that are produced with nasal airflow (nasalized vowels).
-
D.
hasVirama
Indicates that a character or script element is associated with a virama sign, typically used to suppress the inherent vowel or join consonants in abugida writing systems.
-
E.
usesDiacritics
Indicates that the referenced text or linguistic element employs diacritical marks as part of its written form.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58e65e8819098cba7e6a20d8f33 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.