Triple
T26527785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arms of Courtenay (or three torteaux gules) |
E670738
|
entity |
| Predicate | laterUsedInCountry |
P715
|
FINISHED |
| Object | England |
—
|
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: England | Statement: [Arms of Courtenay (or three torteaux gules), laterUsedInCountry, England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterUsedInCountry Context triple: [Arms of Courtenay (or three torteaux gules), laterUsedInCountry, England]
-
A.
usedInCountry
chosen
Indicates that something is utilized, applied, or in operation within the specified country.
-
B.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
-
C.
usedInCountries
Indicates that something is utilized or applied within one or more specified countries.
-
D.
usedForCountry
Indicates that something is used for, or serves a purpose related to, a specific country.
-
E.
usedByCountriesWith
Indicates that something (such as an item, system, or practice) is utilized or employed by one or more specified countries in common.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 27, 2026, 1:33 a.m.