Triple
T7605702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese carrier Chitose |
E180097
|
entity |
| Predicate | typeBeforeConversion |
P16344
|
FINISHED |
| Object | seaplane tender |
—
|
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: seaplane tender | Statement: [Japanese carrier Chitose, typeBeforeConversion, seaplane tender]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeBeforeConversion Context triple: [Japanese carrier Chitose, typeBeforeConversion, seaplane tender]
-
A.
formerType
chosen
Indicates that one entity previously had a certain type, role, or classification but no longer does.
-
B.
methodOfConversion
Indicates the specific process or technique used to transform one form, state, or representation into another.
-
C.
originalType
Indicates that one entity represents the initial or source type from which another entity is derived, transformed, or reclassified.
-
D.
allowsConversionTo
Indicates that one entity permits or enables transformation or change into another specified form or state.
-
E.
eraOfConversion
Indicates the specific historical period or era during which the conversion event or change took place.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9fcfcfc8190a29a0b5cd3e8927a |
completed | March 27, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:54 p.m.