Triple
T22458694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabi-Malayalam |
E555176
|
entity |
| Predicate | notationalFeature |
P6184
|
FINISHED |
| Object | diacritics for Malayalam vowels |
—
|
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: diacritics for Malayalam vowels | Statement: [Arabi-Malayalam, notationalFeature, diacritics for Malayalam vowels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notationalFeature Context triple: [Arabi-Malayalam, notationalFeature, diacritics for Malayalam vowels]
-
A.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
B.
spanFeature
Indicates a relationship where a feature or characteristic extends across or covers a specified span or interval.
-
C.
notation
chosen
Indicates a conventional way of symbolically representing or writing something, such as concepts, quantities, or operations, within a specific system.
-
D.
typicalNotation
Indicates that one entity is the standard or commonly used symbolic representation (notation) for another entity.
-
E.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
- 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b7e01fc8190825c3dc024484440 |
completed | April 29, 2026, 1:14 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:48 p.m.