Triple
T1222127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gujarati script |
E26244
|
entity |
| Predicate | hasISO15924Number |
P25981
|
FINISHED |
| Object | 320 |
—
|
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: 320 | Statement: [Gujarati script, hasISO15924Number, 320]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISO15924Number Context triple: [Gujarati script, hasISO15924Number, 320]
-
A.
ISO15924Status
Indicates the official status or classification of a script according to the ISO 15924 standard.
-
B.
hasISOCode
Indicates that an entity is associated with a specific standardized ISO code that uniquely identifies it according to ISO conventions.
-
C.
hasISOCodeType
Indicates that an entity is associated with a specific type or category of ISO code (e.g., country code, currency code, language code).
-
D.
scriptCodeISO15924
Indicates the script or writing system used to represent text, identified by its ISO 15924 code.
-
E.
hasISO639_5Code
Indicates that a language or language group is associated with a specific ISO 639-5 code that identifies it within the ISO 639-5 language classification standard.
- 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_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be21a2bc819094b47580d7c5cdf8 |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bd3140688190ac6e24de157fd61e |
completed | March 1, 2026, 10:26 p.m. |
Created at: March 1, 2026, 7:47 p.m.