Triple
T1127577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Rennell Island |
E24754
|
entity |
| Predicate | U.S.Losses |
P683
|
FINISHED |
| Object | heavy cruiser USS Chicago sunk |
—
|
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: heavy cruiser USS Chicago sunk | Statement: [Battle of Rennell Island, U.S.Losses, heavy cruiser USS Chicago sunk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: U.S.Losses Context triple: [Battle of Rennell Island, U.S.Losses, heavy cruiser USS Chicago sunk]
-
A.
casualtiesUnitedStates
chosen
Indicates that the event or situation resulted in casualties (deaths and/or injuries) among United States personnel or citizens.
-
B.
aircraftDestroyedUS
Indicates that a U.S. aircraft has been destroyed.
-
C.
casualtiesKilledUS
Indicates that the relationship specifies the number of U.S. individuals who were killed as casualties in an event or incident.
-
D.
aircraftDamagedUS
Indicates that a U.S. aircraft has been damaged, typically as a result of a specific event or action.
-
E.
purchasedByUnitedStatesIn
Indicates that something was bought or acquired by the United States during a specified time period.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb48de2081909a0dce005b1c9df1 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.