Triple
T14424018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lolo-Burmese |
E357649
|
entity |
| Predicate | hasWritingSystem |
P454
|
FINISHED |
| Object | Yi syllabary (for Yi) |
E748954
|
NE 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: Yi syllabary (for Yi) | Statement: [Lolo-Burmese, hasWritingSystem, Yi syllabary (for Yi)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yi syllabary (for Yi) Context triple: [Lolo-Burmese, hasWritingSystem, Yi syllabary (for Yi)]
-
A.
Yi script
chosen
Yi script is a traditional logographic and syllabic writing system used to represent the Yi languages of southwestern China.
-
B.
Hangul Syllables
Hangul Syllables is the Unicode block that encodes the precomposed modern Korean syllabic characters used for writing Hangul.
-
C.
Hangul Jamo
Hangul Jamo is a Unicode block that encodes the individual consonant and vowel letters used to write the Korean Hangul script.
-
D.
Sorabe script
The Sorabe script is an Arabic-derived writing system historically used by Malagasy speakers, particularly in southern Madagascar, for religious, literary, and administrative texts.
-
E.
Hanja
Hanja is the set of traditional Chinese characters historically used to write Korean, especially for proper names, academic terms, and classical texts.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91123f848190ba3fb18a76c2d24c |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcd2a908190ad7d5ebf11b41551 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:18 a.m.