Triple
T561698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Picene alphabet |
E13464
|
entity |
| Predicate | hasDistinctCharacterSet |
P16425
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [South Picene alphabet, hasDistinctCharacterSet, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctCharacterSet Context triple: [South Picene alphabet, hasDistinctCharacterSet, yes]
-
A.
hasSpecialCharacter
Indicates that a given entity (such as a string or identifier) contains at least one non-alphanumeric special character.
-
B.
hasDistinctGrammar
Indicates that the subject’s grammar system is different in structure or rules from that of the object.
-
C.
usesCharacterSet
Indicates that one entity employs or relies on a specific character set defined by another entity for encoding or representing text.
-
D.
hasTypicalCharacterType
Indicates that an entity is commonly associated with or exemplified by a particular type of character or persona.
-
E.
hasDistinctVocabulary
Indicates that one entity’s vocabulary is different or distinguishable from that of another entity.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a700e608190b235246df057bd9b |
completed | March 1, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69a494befb8481908bb4e2e9f31e343b |
completed | March 1, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69a4985952a481908b918350ececf484 |
completed | March 1, 2026, 7:49 p.m. |
Created at: March 1, 2026, 7:32 p.m.