Triple
T691218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Pusan Perimeter |
E13395
|
entity |
| Predicate | opponentObjective |
P16720
|
FINISHED |
| Object | capture Pusan and destroy UN forces |
—
|
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: capture Pusan and destroy UN forces | Statement: [Battle of Pusan Perimeter, opponentObjective, capture Pusan and destroy UN forces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opponentObjective Context triple: [Battle of Pusan Perimeter, opponentObjective, capture Pusan and destroy UN forces]
-
A.
opponentAtMidway
Indicates that one entity is the opposing side or competitor of another in the context of the Midway event, location, or stage.
-
B.
protectionObjective
Indicates that one entity has the goal or purpose of safeguarding, defending, or preserving another entity or its interests.
-
C.
opposingLocation
Indicates that two entities are located directly opposite each other, typically across a defined reference such as a street, corridor, or boundary.
-
D.
keyOpponents
Indicates that the subject has primary or most significant opponents identified by the object.
-
E.
opponentCandidate
Indicates that one entity is a rival or competing candidate against another in the same contest or election.
- 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_69a4933e0f98819097d22766c49b61b8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a0aebde88190a49d421477713103 |
completed | March 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69a49d221d38819083c0adda81f59b07 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49dc20880819085fa60dc1851f9dc |
completed | March 1, 2026, 8:12 p.m. |
Created at: March 1, 2026, 7:36 p.m.