Triple
T22197920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orkh |
E548594
|
entity |
| Predicate | partOfStandard |
P35
|
FINISHED |
| Object | ISO 15924 |
—
|
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: ISO 15924 | Statement: [Orkh, partOfStandard, ISO 15924]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ISO 15924 Context triple: [Orkh, partOfStandard, ISO 15924]
-
A.
ISO 15924
chosen
ISO 15924 is an international standard that assigns four-letter codes to the world’s writing systems and scripts for use in information processing and interchange.
-
B.
ISO/IEC 10646
ISO/IEC 10646 is an international standard that defines the Universal Coded Character Set (UCS), a comprehensive repertoire of characters used worldwide and closely aligned with the Unicode Standard.
-
C.
ECMA-125
ECMA-125 is an ECMA standard that defines the physical and magnetic recording characteristics for 3.5-inch floppy disk media used in microcomputer systems.
-
D.
ISO 639
ISO 639 is an international standard that defines codes for the representation of names of languages.
-
E.
ISO standards for transliteration
ISO standards for transliteration are internationally recognized systems that define how to systematically convert text from various writing systems into Latin characters to ensure consistency and interoperability across languages and applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae8c74c819080c7f9e8383ecaa7 |
completed | April 28, 2026, 9:47 p.m. |
Created at: April 16, 2026, 8:36 p.m.