Triple
T33773202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navin |
E865440
|
entity |
| Predicate | scriptFormLanguage |
P56657
|
FINISHED |
| Object | Devanagari |
—
|
NE NERFINISHED |
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: Devanagari | Statement: [Navin, scriptFormLanguage, Devanagari]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptFormLanguage Context triple: [Navin, scriptFormLanguage, Devanagari]
-
A.
scriptNameLanguage
Indicates that a script’s name is expressed or written in a particular language.
-
B.
scriptVariantLanguage
Indicates that a language is a variant distinguished by its writing system or script from another, related language form.
-
C.
scriptLanguageIdentifier
Indicates the specific programming or scripting language associated with a given script or code artifact.
-
D.
scriptUsedForLanguage
chosen
Indicates that a particular writing script is employed to write or represent a given language.
-
E.
scriptType
Indicates the classification or category of a script, specifying what kind of script it is (e.g., its format, purpose, or scripting language type).
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: May 1, 2026, 1:45 a.m.