Triple
T16028023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 北の丸公園 |
E388767
|
entity |
| Predicate | 歴史的背景 |
P43371
|
FINISHED |
| Object | 江戸城の一部であった区域を戦後に公園化した |
—
|
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: 江戸城の一部であった区域を戦後に公園化した | Statement: [北の丸公園, 歴史的背景, 江戸城の一部であった区域を戦後に公園化した]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 歴史的背景 Context triple: [北の丸公園, 歴史的背景, 江戸城の一部であった区域を戦後に公園化した]
-
A.
historicalBackground
chosen
Indicates that one entity provides contextual historical information or circumstances that help explain the origin, development, or significance of another entity.
-
B.
hasHistoricalContext
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
C.
historicalReason
Indicates that one entity exists, occurs, or is justified because of causes, events, or circumstances rooted in the past of another entity.
-
D.
historicalOrigin
Indicates the relationship by which one entity serves as the source, origin, or starting point in history for another entity.
-
E.
historical
Indicates that the subject has existed, occurred, or been relevant in the past rather than in the present or future.
- 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 4:56 a.m.