Triple
T28806547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bombing of Osaka |
E727389
|
entity |
| Predicate | aircraftBase |
P169968
|
FINISHED |
| Object | Mariana Islands |
—
|
NE NERFINISHED |
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: Mariana Islands | Statement: [Bombing of Osaka, aircraftBase, Mariana Islands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftBase Context triple: [Bombing of Osaka, aircraftBase, Mariana Islands]
-
A.
aircraft
Indicates that an entity is an aircraft or functions in the role of an aircraft in the described context.
-
B.
basedOnAircraft
Indicates that one entity is derived from, modeled after, or otherwise uses a particular aircraft as its basis or primary reference.
-
C.
airframeDerivedFrom
Indicates that one airframe design is derived or developed from another pre-existing airframe design.
-
D.
aircraftType
Indicates the specific model or category of aircraft associated with an entity or event.
-
E.
aircraftIntroduction
Indicates the point in time or context when an aircraft model was first introduced into service or made publicly available.
- 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_69f0319c38948190bca746ad60fd25ba |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f688d015908190ad5df37030ecf332 |
completed | May 2, 2026, 11:29 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f688034580819086a0f9100645f8ba |
completed | May 2, 2026, 11:25 p.m. |
Created at: April 28, 2026, 6:29 a.m.