Triple
T18841497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Bois |
E460806
|
entity |
| Predicate | hasRegionCodeISO_3166_2 |
P42695
|
FINISHED |
| Object | CH-JU |
—
|
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: CH-JU | Statement: [Les Bois, hasRegionCodeISO_3166_2, CH-JU]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionCodeISO_3166_2 Context triple: [Les Bois, hasRegionCodeISO_3166_2, CH-JU]
-
A.
ISO3166-2RegionCode
chosen
Indicates the standardized ISO 3166-2 code that specifies the particular primary administrative subdivision (such as a state, province, or region) to which an entity belongs.
-
B.
hasRegionCode
Indicates that an entity is associated with a specific regional identifier or code.
-
C.
associatedCountrySubdivisionCode
Indicates the specific administrative region or subdivision code within a country that is linked to or relevant for the given entity.
-
D.
associatedSubdivisionISO3166-1Alpha2
Indicates that a subdivision (such as a state or province) is associated with a specific country identified by its ISO 3166-1 alpha-2 code.
-
E.
subregionCodeFor
Indicates that one entity is the code assigned to identify a specific subregion of the other entity.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5b8ea35c88190af6659551ad18130 |
completed | April 20, 2026, 5:26 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:56 a.m.