Triple
T186408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | district courts of Japan |
E3990
|
entity |
| Predicate | hasMainCourts |
P6713
|
FINISHED |
| Object | one in each prefecture |
—
|
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: one in each prefecture | Statement: [district courts of Japan, hasMainCourts, one in each prefecture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainCourts Context triple: [district courts of Japan, hasMainCourts, one in each prefecture]
-
A.
numberOfCourts
Indicates the quantity of courts associated with or present at a given entity or location.
-
B.
mainStadium
Indicates that a particular stadium serves as the primary or home stadium associated with an entity (such as a team, club, or organization).
-
C.
hasMainOrgan
Indicates that an entity possesses a primary or principal organ that plays a central role in its biological or functional system.
-
D.
hasMajorMarket
Indicates that an entity has a primary or most significant market in a specified location or segment.
-
E.
hasMainStreet
Indicates that a place or locality possesses a primary street commonly recognized as its main thoroughfare.
- F. None of above. chosen
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_69a25497e2f08190a040f8c6e1842643 |
completed | Feb. 28, 2026, 2:36 a.m. |
| NER | Named-entity recognition | batch_69a2594809288190b3d3b1283e7e0d00 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25670feb081908e26a2543ebe7b3a |
completed | Feb. 28, 2026, 2:44 a.m. |
| PDg | Predicate description generation | batch_69a257e763d081908c54ad57d8d3060d |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:40 a.m.