Triple
T372733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Württemberg |
E8303
|
entity |
| Predicate | countryCodeTopLevelDomain |
P11776
|
FINISHED |
| Object | .de |
—
|
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: .de | Statement: [Kingdom of Württemberg, countryCodeTopLevelDomain, .de]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryCodeTopLevelDomain Context triple: [Kingdom of Württemberg, countryCodeTopLevelDomain, .de]
-
A.
ISOCode
Indicates that an entity is associated with a specific standardized code defined by the International Organization for Standardization (ISO).
-
B.
countryDeJure
Indicates that one entity is the legally recognized (de jure) country having sovereignty or authority over another entity.
-
C.
UNLOCODECountryCode
Indicates that an entity is associated with a specific country code as defined by the UN/LOCODE standard.
-
D.
countryOrTerritory
Indicates that one entity is a country or territory associated with, or characterized by, another entity.
-
E.
associatedCountry
Indicates that there is a relevant connection or linkage between an entity and a specific country, such as origin, operation, or affiliation.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec018d508190b5687a9ba90b3092 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e960d880819084b3df4e5137a1e2 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea0b23ec8190bef9d593162388a4 |
completed | Feb. 28, 2026, 1:13 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.