Triple
T13246417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAM 28000 |
E315416
|
entity |
| Predicate | crewComplementClass |
P88726
|
FINISHED |
| Object | large crew |
—
|
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: large crew | Statement: [SAM 28000, crewComplementClass, large crew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: crewComplementClass Context triple: [SAM 28000, crewComplementClass, large crew]
-
A.
crewComplementType
chosen
Indicates the classification or category of a crew complement associated with an entity (such as its role, composition, or staffing type).
-
B.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
C.
crewOnboard
Indicates that a person or group is serving as crew aboard a specific vehicle, vessel, or craft.
-
D.
crewOfficers
Indicates that the subject is an officer serving as part of the crew of the object (e.g., a vessel, unit, or organization).
-
E.
crew
Indicates that one entity serves as the group of people who operate, staff, or work on another entity (such as a vehicle, vessel, or production).
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5c09f88190bb1566a6d8c073a6 |
completed | April 10, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:23 p.m.