Triple
T14671279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shenhai Yongshi |
E344516
|
entity |
| Predicate | hasCrewComposition |
P88726
|
FINISHED |
| Object | 1 pilot and 2 observers |
—
|
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: 1 pilot and 2 observers | Statement: [Shenhai Yongshi, hasCrewComposition, 1 pilot and 2 observers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrewComposition Context triple: [Shenhai Yongshi, hasCrewComposition, 1 pilot and 2 observers]
-
A.
hasCrewRole
Indicates that an entity serves in a specific role or position within a crew associated with another entity.
-
B.
crewOnboard
Indicates that a person or group is serving as crew aboard a specific vehicle, vessel, or craft.
-
C.
hasCrewMember
Indicates that an entity includes or employs another entity as a member of its crew.
-
D.
crewComplementType
chosen
Indicates the classification or category of a crew complement associated with an entity (such as its role, composition, or staffing type).
-
E.
featureCrew
Indicates that a particular crew member is highlighted or designated as a featured participant within a crew-related context.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb54ef2908190b189ced65eec434a |
completed | April 14, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69de6576f0208190aa94d995e797ac38 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.