Triple
T24552811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Wackiest Ship in the Army |
E607417
|
entity |
| Predicate | titleCharacterVessel |
P110548
|
FINISHED |
| Object | USS Echo |
—
|
NE NERFINISHED |
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: USS Echo | Statement: [The Wackiest Ship in the Army, titleCharacterVessel, USS Echo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleCharacterVessel Context triple: [The Wackiest Ship in the Army, titleCharacterVessel, USS Echo]
-
A.
namedVesselOf
chosen
Indicates that one entity is the specific named vessel (e.g., ship, boat, or craft) associated with or belonging to another entity.
-
B.
vesselDepicted
Indicates that a vessel (such as a ship, boat, or similar watercraft) is shown or represented in the subject entity.
-
C.
shipName
Indicates the name assigned to a specific ship in the relationship.
-
D.
titleCharacterDestination
Indicates the destination or endpoint that the title character is intended to reach or is associated with in the context of the narrative or action.
-
E.
featuresVessel
Indicates that one entity includes, presents, or prominently displays a particular vessel as part of its composition, content, or configuration.
- 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_69e2c4cae1b88190825e88d5ce8aa61e |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2a8cf1ef88190977da0fb79796616 |
completed | April 30, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b99e7c8190ba7e2dc8729a314a |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:27 a.m.