Triple
T8646661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FAL Form 4 – Crew’s Effects Declaration |
E204992
|
entity |
| Predicate | canBeTranslatedInto |
P45244
|
FINISHED |
| Object | national languages of port states |
—
|
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: national languages of port states | Statement: [FAL Form 4 – Crew’s Effects Declaration, canBeTranslatedInto, national languages of port states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canBeTranslatedInto Context triple: [FAL Form 4 – Crew’s Effects Declaration, canBeTranslatedInto, national languages of port states]
-
A.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
B.
hasWorkTranslatedInto
chosen
Indicates that a work has been translated into a specified language or target work.
-
C.
languageTranslatedFrom
Indicates that a language is the source/original language from which content has been translated into another language.
-
D.
hasTranslated
Indicates that one entity has rendered the content of another entity from one language into a different language.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc480eb7f88190a38d2150976cd47f |
completed | March 31, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69cc45619460819091e83ffdec99c865 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.