Triple
T30349658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eita Kidou |
E771956
|
entity |
| Predicate | hasChildhoodFriend |
P57640
|
FINISHED |
| Object | Chiwa Harusaki |
—
|
NE NERFINISHED |
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: Chiwa Harusaki | Statement: [Eita Kidou, hasChildhoodFriend, Chiwa Harusaki]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChildhoodFriend Context triple: [Eita Kidou, hasChildhoodFriend, Chiwa Harusaki]
-
A.
childhoodFriend
chosen
Indicates that two people were close friends during their childhood period.
-
B.
hasYoungerFriend
Indicates that one person has a friend who is younger than they are.
-
C.
hasFriends
Indicates that an entity is socially connected to one or more other entities in a friendship relationship.
-
D.
hasFamilyFriend
Indicates that one entity has another entity as a friend who is connected through family ties or close familial relationships.
-
E.
isChildhoodSweetheartOf
Indicates that two people were romantically involved with each other during their childhood or adolescence, typically as first or early sweethearts.
- 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_69f2248b9a208190bc3e6804acd5afd6 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: April 29, 2026, 7:56 p.m.