Triple
T6749571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NL |
E154307
|
entity |
| Predicate | countryKnownFor |
P73284
|
FINISHED |
| Object | flat landscape |
—
|
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: flat landscape | Statement: [NL, countryKnownFor, flat landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryKnownFor Context triple: [NL, countryKnownFor, flat landscape]
-
A.
countryExample
Indicates that one country serves as a representative or illustrative example of another country in a given context.
-
B.
countryFeatured
Indicates that a particular country is highlighted or given special prominence in a given context or presentation.
-
C.
capitalCountry
Indicates that one place serves as the capital city of a given country.
-
D.
country1
Indicates that the subject entity is a country (or represents a country) in the given context.
-
E.
country2
Indicates a secondary or alternative country associated with an entity, such as a second nationality, location, or jurisdiction.
- 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_69c6880ef37881909268a5a7299b9293 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
| PDg | Predicate description generation | batch_69c6d3264b7481908816a4d19543fb7b |
completed | March 27, 2026, 6:57 p.m. |
Created at: March 27, 2026, 2:11 p.m.