Triple
T284007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Convention for the Safety of Life at Sea |
E5848
|
entity |
| Predicate | containsChapterOn |
P6720
|
FINISHED |
| Object | general provisions |
—
|
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: general provisions | Statement: [International Convention for the Safety of Life at Sea, containsChapterOn, general provisions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsChapterOn Context triple: [International Convention for the Safety of Life at Sea, containsChapterOn, general provisions]
-
A.
containsChapter
chosen
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
C.
numberOfChapters
Indicates the total count of chapters associated with a given entity.
-
D.
containsBook
Indicates that one entity (typically a container or collection) includes a specific book as part of its contents.
-
E.
containsArticle
Indicates that one entity includes or holds an article (such as a written piece, item, or document) as part of its contents.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e0d789881908d6a9a8d6a0d4a6c |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b795a6c8190944d48e8418e0ccd |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.