Triple
T37619573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince of Robecque |
E936025
|
entity |
| Predicate | titleOriginCountry |
P201463
|
FINISHED |
| Object | Kingdom of 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: Kingdom of France | Statement: [Prince of Robecque, titleOriginCountry, Kingdom of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleOriginCountry Context triple: [Prince of Robecque, titleOriginCountry, Kingdom of France]
-
A.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
-
B.
engineOriginCountry
Indicates the country where an engine was originally designed, manufactured, or first produced.
-
C.
organizationCountryOfOrigin
Indicates the country where an organization was originally founded or established.
-
D.
countryOfCatalogueOrigin
Indicates the country where a catalogue was originally created, issued, or first published.
-
E.
orderCountryOfOrigin
Indicates the country from which an order was originally placed, sourced, or shipped.
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fff86e544c81908063f61b876c9d78 |
completed | May 10, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fff7e7cb688190977eeca41aad25b9 |
completed | May 10, 2026, 3:13 a.m. |
| PDg | Predicate description generation | batch_69fff86da6f48190aac10a80b648c05a |
completed | May 10, 2026, 3:15 a.m. |
Created at: May 3, 2026, 4:18 p.m.