Triple
T34159272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ever |
E876227
|
entity |
| Predicate | shipTypeScope |
P8971
|
FINISHED |
| Object | Evergreen-operated container ships only |
—
|
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: Evergreen-operated container ships only | Statement: [Ever, shipTypeScope, Evergreen-operated container ships only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipTypeScope Context triple: [Ever, shipTypeScope, Evergreen-operated container ships only]
-
A.
shipTypeFavored
Indicates that a particular type of ship is preferred or favored over others in a given context.
-
B.
shipTypeInvolved
chosen
Indicates that a particular type or class of ship is involved or participates in a specified event, situation, or relationship.
-
C.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
D.
shipRepresents
Indicates that one entity (typically a ship) serves as a symbol, stand-in, or representation for another entity, concept, or group.
-
E.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
- 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_69f349ac987481908a8e6053f665bc8b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fdedf708190ab68c2d567e086d0 |
completed | May 3, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:54 a.m.