Triple
T33608055
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mississippi Squadron |
E860912
|
entity |
| Predicate | notableVesselType |
P205236
|
FINISHED |
| Object | City-class ironclad gunboat |
—
|
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: City-class ironclad gunboat | Statement: [Mississippi Squadron, notableVesselType, City-class ironclad gunboat]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableVesselType Context triple: [Mississippi Squadron, notableVesselType, City-class ironclad gunboat]
-
A.
notableVesselBuilt
Indicates that a particular vessel was constructed by or for the subject and is notable or significant in that context.
-
B.
namedVesselOf
Indicates that one entity is the specific named vessel (e.g., ship, boat, or craft) associated with or belonging to another entity.
-
C.
notableShip
Indicates that there is a notable or significant ship associated with the subject entity.
-
D.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
E.
notableBoatClass
Indicates that the subject is a notable or significant example of the specified class or type of boat.
- F. None of above. chosen
Provenance (4 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_69f3498037c88190a4500f002b5540e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f505c88190ac0879ab422c3054 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:41 a.m.