Triple
T127876
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaga |
E2588
|
entity |
| Predicate | roleAtPearlHarbor |
P6550
|
FINISHED |
| Object | launched carrier air strikes on U.S. Pacific Fleet |
—
|
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: launched carrier air strikes on U.S. Pacific Fleet | Statement: [Kaga, roleAtPearlHarbor, launched carrier air strikes on U.S. Pacific Fleet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtPearlHarbor Context triple: [Kaga, roleAtPearlHarbor, launched carrier air strikes on U.S. Pacific Fleet]
-
A.
commemoratesRoleAs
Indicates that something serves to honor or recognize a specific role or position held by an entity.
-
B.
sideInWorldWarII
Indicates that an entity was aligned with or participated on a particular side during World War II.
-
C.
servedAs
Indicates that one entity held and performed the role, position, or function associated with another entity for some period of time.
-
D.
codenameOfLandings
Indicates that one entity is the codename assigned to a specific set of landings or landing operations.
-
E.
commanderJapan
Indicates that an entity serves as the military commander of Japan or of Japanese forces.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a25763ccf8819094e8dffb2ff98480 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564c11208190ad25495609d94d87 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2575d8a648190ad8e10d4b04e5e07 |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.