Triple
T4562771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chemins de fer fédéraux suisses |
E121833
|
entity |
| Predicate | UICCountryCode |
P57691
|
FINISHED |
| Object | 85 |
—
|
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: 85 | Statement: [Chemins de fer fédéraux suisses, UICCountryCode, 85]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UICCountryCode Context triple: [Chemins de fer fédéraux suisses, UICCountryCode, 85]
-
A.
FIPSCountryCode
Indicates that an entity is associated with a specific country as identified by its FIPS (Federal Information Processing Standards) country code.
-
B.
countryCodePart
Indicates that one entity is a segment or component of a standardized country code associated with another entity.
-
C.
callingCode
Indicates the telephone country or area code associated with an entity for making phone calls.
-
D.
callingCodeType
Indicates the type or category of a telephone calling code associated with an entity.
-
E.
countryCodeManaged
Indicates that an entity is responsible for administering or controlling the specified country code.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd5830b4308190a63699bf28922375 |
completed | March 20, 2026, 2:22 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56f6e75481909c487a94a2c2d0ba |
completed | March 20, 2026, 2:17 p.m. |
Created at: March 20, 2026, 1:09 p.m.