Triple
T4301582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Picene language |
E99848
|
entity |
| Predicate | hasUncertainVocabulary |
P55340
|
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: [North Picene language, hasUncertainVocabulary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUncertainVocabulary Context triple: [North Picene language, hasUncertainVocabulary, true]
-
A.
hasUncertainty
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
B.
hasKnownVocabulary
Indicates that an entity possesses a defined, identifiable set of terms or words that it can recognize or use.
-
C.
hasVocabularyFrom
Indicates that one entity’s vocabulary, terminology, or set of terms is derived from, based on, or taken from another entity.
-
D.
hasDistinctVocabulary
Indicates that one entity’s vocabulary is different or distinguishable from that of another entity.
-
E.
hasUnknown
Indicates that an entity possesses or is associated with information, attributes, or values that are not known or not specified.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3509fb2b88190a13ab88a5b924052 |
completed | March 12, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69b347fe55a88190b77bab0c0f38e1aa |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e0606488190baadf469a1afc3c2 |
completed | March 12, 2026, 11:36 p.m. |
Created at: March 12, 2026, 11:08 p.m.