Triple
T30811417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Masuzu Natsukawa |
E784653
|
entity |
| Predicate | formsRelationshipType |
P10690
|
FINISHED |
| Object | fake girlfriend of Eita Kidou |
—
|
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: fake girlfriend of Eita Kidou | Statement: [Masuzu Natsukawa, formsRelationshipType, fake girlfriend of Eita Kidou]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsRelationshipType Context triple: [Masuzu Natsukawa, formsRelationshipType, fake girlfriend of Eita Kidou]
-
A.
relationshipType
chosen
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipTypeStart
Indicates the type or category of relationship that begins or is initiated at a specific point or event.
-
C.
unitRelation
Indicates a relationship between units, such as how one unit is associated with, derived from, or converted to another.
-
D.
coversRelationship
Indicates that one entity extends over, includes, or provides encompassing coverage for another entity or set of entities.
-
E.
reportsRelationship
Indicates that one entity formally provides information, findings, or status about another entity or situation.
- 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_69f224b4eda48190bd212ce4f3901e56 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: April 29, 2026, 8:43 p.m.