Triple
T256144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Leyte Gulf |
E5440
|
entity |
| Predicate | shipTypeInvolved |
P8971
|
FINISHED |
| Object | aircraft carriers |
—
|
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: aircraft carriers | Statement: [Battle of Leyte Gulf, shipTypeInvolved, aircraft carriers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipTypeInvolved Context triple: [Battle of Leyte Gulf, shipTypeInvolved, aircraft carriers]
-
A.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
-
B.
shipClass
Indicates the classification or type category to which a particular ship belongs.
-
C.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
D.
numberOfShipsInvolved
Indicates the total count of ships that participated or were involved in a specified event or situation.
-
E.
fleetType
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d5669008190978bbd7308be11f7 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c4b773c81908f1017f40b0bfd07 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.