Triple
T4759898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeta |
E105673
|
entity |
| Predicate | ISO15924CodeForScript |
P11937
|
FINISHED |
| Object | Grek |
—
|
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: Grek | Statement: [Zeta, ISO15924CodeForScript, Grek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISO15924CodeForScript Context triple: [Zeta, ISO15924CodeForScript, Grek]
-
A.
scriptCodeISO15924
chosen
Indicates the script or writing system used to represent text, identified by its ISO 15924 code.
-
B.
ISO15924Status
Indicates the official status or classification of a script according to the ISO 15924 standard.
-
C.
hasISO15924Number
Indicates that an entity (a writing script) is associated with a specific numeric code defined by the ISO 15924 standard.
-
D.
hasUnicodeScript
Indicates that a character or text element belongs to a specific Unicode script category (such as Latin, Cyrillic, or Han).
-
E.
associatedLanguageScript
Indicates that there is a relationship between a language and the script or writing system used to represent it.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650dc7fc81909b483ef3c456ae0d |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.