Triple
T3730577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom in the Sky |
E79050
|
entity |
| Predicate | countryTypeDescribed |
P5544
|
FINISHED |
| Object | landlocked country |
—
|
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: landlocked country | Statement: [Kingdom in the Sky, countryTypeDescribed, landlocked country]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryTypeDescribed Context triple: [Kingdom in the Sky, countryTypeDescribed, landlocked country]
-
A.
countryType
chosen
Indicates the classification or category of a country based on a specified typology (e.g., political, economic, or geographic type).
-
B.
countrySubject
Indicates that the subject entity is a country that is the main actor, topic, or focus in the described relation or statement.
-
C.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
D.
country2
Indicates a secondary or alternative country associated with an entity, such as a second nationality, location, or jurisdiction.
-
E.
countryFeatured
Indicates that a particular country is highlighted or given special prominence in a given context or presentation.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb1bb5408190990ea4dfbdab5c68 |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.