Triple
T719387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Picene alphabet |
E14381
|
entity |
| Predicate | ISO15924Status |
P18506
|
FINISHED |
| Object | no ISO 15924 code |
—
|
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: no ISO 15924 code | Statement: [North Picene alphabet, ISO15924Status, no ISO 15924 code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISO15924Status Context triple: [North Picene alphabet, ISO15924Status, no ISO 15924 code]
-
A.
scriptCodeISO15924
Indicates the script or writing system used to represent text, identified by its ISO 15924 code.
-
B.
ISO639_3Status
Indicates the classification or status assigned to a language according to the ISO 639-3 standard (e.g., active, extinct, historical, constructed).
-
C.
hasUnicodeStatus
Indicates that a given entity has a particular Unicode-related classification or status (such as assigned, reserved, deprecated, or noncharacter) within the Unicode standard.
-
D.
standardizationStatus
Indicates the current stage or condition of an entity in a formal standardization process (e.g., proposed, under review, approved, deprecated).
-
E.
hasISO6393Code
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
- 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58e65e8819098cba7e6a20d8f33 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.