Triple
T13619583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | In altre parole |
E325411
|
entity |
| Predicate | hasParallelText |
P2303
|
FINISHED |
| Object | Italian and English |
—
|
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: Italian and English | Statement: [In altre parole, hasParallelText, Italian and English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParallelText Context triple: [In altre parole, hasParallelText, Italian and English]
-
A.
hasTranslation
chosen
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasMultilingualDialogue
Indicates that an interaction or work contains dialogue expressed in more than one language.
-
C.
hasParallelIn
Indicates that one entity has a corresponding or analogous counterpart in another context, system, or domain.
-
D.
hasParallelCitation
Indicates that one legal case or document is cited in multiple sources or reporters that refer to the same underlying authority.
-
E.
hasLanguageOfSide
Indicates that an entity uses or is associated with a particular language on a specific side or aspect (e.g., one side of a bilingual object or interface).
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.