Triple
T656132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oscan alphabet |
E11651
|
entity |
| Predicate | hasDistinctLetterFormsFor |
P9189
|
FINISHED |
| Object | Oscan phonemes |
—
|
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: Oscan phonemes | Statement: [Oscan alphabet, hasDistinctLetterFormsFor, Oscan phonemes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctLetterFormsFor Context triple: [Oscan alphabet, hasDistinctLetterFormsFor, Oscan phonemes]
-
A.
hasContextualLetterForms
chosen
Indicates that the written form of a letter changes shape depending on its surrounding characters or position within a word.
-
B.
hasThreeLetterForm
Indicates that an entity’s written or symbolic form consists of exactly three letters.
-
C.
hasPronunciationDifferenceFrom
Indicates that two linguistic items differ in how they are pronounced.
-
D.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
E.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f4e87408190b5276d2b913d0426 |
completed | March 1, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69a49d121cec81909986c91291bb4ca8 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.