Triple
T2803744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese aircraft carrier Ryūjō |
E54003
|
entity |
| Predicate | modification |
P43320
|
FINISHED |
| Object | hull deepened to improve stability |
—
|
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: hull deepened to improve stability | Statement: [Japanese aircraft carrier Ryūjō, modification, hull deepened to improve stability]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modification Context triple: [Japanese aircraft carrier Ryūjō, modification, hull deepened to improve stability]
-
A.
sentenceModification
Indicates that one sentence alters, qualifies, or elaborates on the meaning, structure, or content of another sentence.
-
B.
revisionMechanism
Indicates the method or process by which something is updated, corrected, or modified over time.
-
C.
revisionOf
Indicates that one entity is a modified or updated version of another earlier entity.
-
D.
leafModification
Indicates a relationship where an entity undergoes or causes a change in the structure, form, or characteristics of a leaf.
-
E.
decorChanges
Indicates that an entity alters or updates the decorative appearance or arrangement of another entity or environment.
- 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_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde2ec2ac8190bd702ad3eafb6aed |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd059f308190853191f6ffe2bc6f |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde2cdcc48190827195d3ae70aa19 |
completed | March 7, 2026, 8:13 a.m. |
Created at: March 6, 2026, 9:59 p.m.