Triple
T24684989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europe/Paris |
E611256
|
entity |
| Predicate | primaryReferenceCountry |
P159374
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Europe/Paris, primaryReferenceCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryReferenceCountry Context triple: [Europe/Paris, primaryReferenceCountry, France]
-
A.
primaryLocationCountry
Indicates the country that serves as the main or primary location associated with the subject.
-
B.
primaryRouteCountry
Indicates the country that serves as the main or principal route location associated with the subject.
-
C.
primaryUseCountry
Indicates the country in which something is primarily used or most commonly utilized.
-
D.
nativeCountry
Indicates the country in which an entity (typically a person) was born or is originally from.
-
E.
primaryAncestralCountry
Indicates the country that is considered the main place of origin for an individual’s or group’s ancestors.
- 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_69e2c4d678b081908910f4271627a31a |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f584f07b648190aee894c1d5320bc3 |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 18, 2026, 3:17 a.m.