Triple
T6907093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aztec pictographic writing |
E159838
|
entity |
| Predicate | notFullyPhonetic |
P74045
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Aztec pictographic writing, notFullyPhonetic, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notFullyPhonetic Context triple: [Aztec pictographic writing, notFullyPhonetic, true]
-
A.
isPhonetic
Indicates that one entity represents the phonetic (sound-based) form or pronunciation of another entity.
-
B.
usesPhoneticSystem
Indicates that one entity employs or is based on a particular phonetic system for representing or encoding sounds.
-
C.
partlyRomanized
Indicates that an entity has been converted into the Roman (Latin) script only in part, with some portions remaining in another script or unchanged.
-
D.
hasPhonologicalBasisFor
Indicates that one entity serves as the phonological source, motivation, or foundation for another entity.
-
E.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
- 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_69c68839ccb88190b4aa5cc1aca3448f |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d98c3ab08190a1830c45578056ac |
completed | March 27, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b93d688190a297244ce81b67ac |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:25 p.m.