Triple
T22050267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nüshu |
E544863
|
entity |
| Predicate | graphemeShape |
P1464
|
FINISHED |
| Object | slender |
—
|
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: slender | Statement: [Nüshu, graphemeShape, slender]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: graphemeShape Context triple: [Nüshu, graphemeShape, slender]
-
A.
graphemeInventory
Indicates the set of distinct written symbols or characters used in a language or writing system.
-
B.
graphemicUnit
Indicates a relationship where one element functions as a basic written symbol or character unit within a writing system.
-
C.
hasGraphemeToPhonemeRelation
Indicates a relationship where a written symbol or sequence of symbols (grapheme) is systematically associated with a corresponding sound or sequence of sounds (phoneme).
-
D.
glottographicType
Indicates the type or nature of a writing or script system used to represent language glottographically.
-
E.
shape
chosen
Indicates that one entity has a particular geometric or physical form characterized by the other 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128323fb08190b9592fd08a96cba0 |
completed | April 28, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69e6f643ca74819083e8ab78e843f243 |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 8:26 p.m.