Triple
T36964486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Psycho Break |
E914390
|
entity |
| Predicate | countryTitleVariant |
P63571
|
FINISHED |
| Object | Japan |
E174
|
NE 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: Japan | Statement: [Psycho Break, countryTitleVariant, Japan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryTitleVariant Context triple: [Psycho Break, countryTitleVariant, Japan]
-
A.
countrySpecificName
Indicates that an entity has a name or label that is specific to, or used within, a particular country.
-
B.
countryUsesTitleInLanguage
Indicates that a country uses a particular official or formal title expressed in a specified language.
-
C.
countryVariant
chosen
Indicates that one entity is a country-specific variant or localized version of another entity.
-
D.
countryNameStyle
Indicates how the name of a country is formatted or styled in a given context.
-
E.
countryAppellationSystem
Indicates a relationship where a country is associated with or defines a particular appellation system for classifying and regulating products (such as wines or foods).
- F. None of above.
Provenance (4 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a033ed9322c8190be994a8d99761caa |
completed | May 12, 2026, 2:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e2c29f6008190a49564e59360ca36 |
completed | June 26, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_6a033df2b254819082a672859e5168e6 |
completed | May 12, 2026, 2:49 p.m. |
Created at: May 3, 2026, 4:14 p.m.