Triple
T1268522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kanto Massacre of Koreans |
E15656
|
entity |
| Predicate | alsoTargetedGroup |
P10541
|
FINISHED |
| Object | Chinese residents in Japan |
—
|
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: Chinese residents in Japan | Statement: [Kanto Massacre of Koreans, alsoTargetedGroup, Chinese residents in Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoTargetedGroup Context triple: [Kanto Massacre of Koreans, alsoTargetedGroup, Chinese residents in Japan]
-
A.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
B.
coveredGroup
Indicates that one group or set is included within, or has its members protected or accounted for by, another group or arrangement.
-
C.
belongsToGroup
Indicates that an entity is a member of, or is included within, a particular group or collection.
-
D.
hasTarget
Indicates that one entity is directed toward, aimed at, or intended to affect another specific entity as its target.
-
E.
interactsWithGroup
Indicates that an entity engages in actions or exchanges with a collective group of other entities.
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c0396e048190b4e2d7aab19268b3 |
completed | March 1, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69a4bede52a081909665d60acbe41d31 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:50 p.m.