Triple
T6671855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese cruiser Furutaka |
E151748
|
entity |
| Predicate | reconstructionFeatures |
P20997
|
FINISHED |
| Object | new superstructure |
—
|
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: new superstructure | Statement: [Japanese cruiser Furutaka, reconstructionFeatures, new superstructure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reconstructionFeatures Context triple: [Japanese cruiser Furutaka, reconstructionFeatures, new superstructure]
-
A.
reconstructionFeature
chosen
Indicates that one entity serves as a feature, component, or characteristic used in the reconstruction or restoration of another entity.
-
B.
reconstructionFor
Indicates that one entity serves as a reconstruction, restoration, or rebuilt version of another entity.
-
C.
reconstructionMethod
Indicates the technique or process used to reconstruct, restore, or rebuild something from its original or fragmented state.
-
D.
reconstructedIn
Indicates that something has been rebuilt, restored, or re-created within a particular context, location, or medium.
-
E.
reconstructs
Indicates performing an action to rebuild, restore, or reassemble something from its parts, damage, or prior state.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.