Triple
T27329872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stolp |
E689765
|
entity |
| Predicate | countryInWhichNameWasUsed |
P154953
|
FINISHED |
| Object | Germany |
—
|
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: Germany | Statement: [Stolp, countryInWhichNameWasUsed, Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryInWhichNameWasUsed Context triple: [Stolp, countryInWhichNameWasUsed, Germany]
-
A.
countryClaimNameUsedBy
Indicates that a particular country name is used or asserted by a specific party as the name for a given territory or country.
-
B.
countryNameUsage
Indicates how a country’s name is used or applied in a particular context or representation.
-
C.
usedNameOfCountry
Indicates that one entity referred to or employed a particular name or designation for a country.
-
D.
hasNameUsageCountry
chosen
Indicates that a particular name is used or recognized within a specified 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_69ef355d4cb08190ab032c0a2e7d3753 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 27, 2026, 11:37 a.m.