Triple
T18584518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Robot Wars series |
E454200
|
entity |
| Predicate | localizationRegion |
P387
|
FINISHED |
| Object | Southeast Asia |
—
|
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: Southeast Asia | Statement: [Super Robot Wars series, localizationRegion, Southeast Asia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localizationRegion Context triple: [Super Robot Wars series, localizationRegion, Southeast Asia]
-
A.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
B.
locale
chosen
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
C.
alsoInLanguageRegion
Indicates that two or more entities are located within or associated with the same language-defined geographic region.
-
D.
longitudeRegion
Indicates that an entity is located within or associated with a specific longitudinal region on the Earth’s surface.
-
E.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
- 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_69d8d38ae7e081908a98df1251842402 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e545b0dff08190a3be481faec34a3c |
completed | April 19, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69e478c98d4c81909d37a0e72c6e7bd0 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:44 a.m.