Triple
T5460456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Persian cuneiform |
E122581
|
entity |
| Predicate | hasLogogramFor |
P32395
|
FINISHED |
| Object | "king" |
—
|
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: "king" | Statement: [Old Persian cuneiform, hasLogogramFor, "king"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLogogramFor Context triple: [Old Persian cuneiform, hasLogogramFor, "king"]
-
A.
usesLogogramsFrom
chosen
Indicates that one writing system or notation incorporates or employs logographic characters originating from another system.
-
B.
hasTraditionalCharacter
Indicates that an entity is associated with or represented by a traditional (non-simplified or historically established) written character form.
-
C.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
D.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
-
E.
hasSyllabary
Indicates that one entity possesses or is associated with a specific syllabary writing system used to represent its language or notation.
- 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_69bd4643f16081908d7f29e08096115a |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.