Triple
T22440442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 半蔵門 |
E554739
|
entity |
| Predicate | 防御上の役割 |
P13143
|
FINISHED |
| Object | 江戸城西側防御の一部 |
—
|
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: 江戸城西側防御の一部 | Statement: [半蔵門, 防御上の役割, 江戸城西側防御の一部]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 防御上の役割 Context triple: [半蔵門, 防御上の役割, 江戸城西側防御の一部]
-
A.
defensiveRole
chosen
Indicates that an entity serves a protective or guarding function in relation to another entity or context.
-
B.
defenseIncludes
Indicates that a defense strategy, plan, or system contains or incorporates a particular component, measure, or element as part of it.
-
C.
builtToDefendAgainst
Indicates that something was constructed or designed specifically for the purpose of protecting against or countering a particular threat, entity, or type of attack.
-
D.
defense
Indicates an action or relationship in which an entity protects, guards, or resists against a threat, attack, or criticism from another entity.
-
E.
providesDefence
Indicates that one entity offers protection or defensive support to another entity.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ae1f82881908a611f134eb03f3d |
completed | April 29, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.