Triple
T569259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kawi script |
E13623
|
entity |
| Predicate | hasCombiningMarks |
P16120
|
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: [Kawi script, hasCombiningMarks, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCombiningMarks Context triple: [Kawi script, hasCombiningMarks, true]
-
A.
hasUnicodeScript
Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
-
B.
hasUnicodeName
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
-
C.
hasLigatures
Indicates that one writing system, font, or text includes combined character forms (ligatures) that join two or more individual glyphs into a single symbol.
-
D.
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.
-
E.
hasCursiveJoining
Indicates that one written character is connected to another through cursive-style joining.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b0406d481908af5fc7bc67103fb |
completed | March 1, 2026, 8:01 p.m. |
| PD | Predicate disambiguation | batch_69a494c2caac819086ab316fa49d324c |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a498dd579081908e02368a4c5efc8c |
completed | March 1, 2026, 7:51 p.m. |
Created at: March 1, 2026, 7:33 p.m.