Triple
T283955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Facilitation Committee |
E5847
|
entity |
| Predicate | workArea |
P1527
|
FINISHED |
| Object | arrival and departure formalities for ships |
—
|
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: arrival and departure formalities for ships | Statement: [Facilitation Committee, workArea, arrival and departure formalities for ships]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workArea Context triple: [Facilitation Committee, workArea, arrival and departure formalities for ships]
-
A.
area
Indicates that one entity has a measured two-dimensional extent or surface size quantified by another entity.
-
B.
worksWithOffice
Indicates that an entity collaborates or is professionally associated with a particular office or office-based organization.
-
C.
locationOfWork
chosen
Indicates the place or site where an entity performs its work or carries out its professional activities.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
- 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.