Triple
T3116684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lao script |
E65078
|
entity |
| Predicate | toneMarkFunction |
P45436
|
FINISHED |
| Object | indicates lexical tone in Lao |
—
|
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: indicates lexical tone in Lao | Statement: [Lao script, toneMarkFunction, indicates lexical tone in Lao]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toneMarkFunction Context triple: [Lao script, toneMarkFunction, indicates lexical tone in Lao]
-
A.
hasPhonemicTone
Indicates that a language, word, or syllable uses pitch differences (tones) as phonemic contrasts that can change meaning.
-
B.
marksStylisticShiftFrom
Indicates that one element signals a change in style, tone, or manner relative to another element.
-
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.
marksShiftToward
Indicates a change or transition from one state, condition, or position toward another, highlighting the direction or trend of that shift.
-
E.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e5d1488190a2ab199625fdf05d |
completed | March 8, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_69ad9df455088190940ad04419772dc8 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f7c21c819087e9992f5fe30a37 |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:04 p.m.