Triple
T24351429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MA |
E613798
|
entity |
| Predicate | cityLocatedInCountry |
P33511
|
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: [MA, cityLocatedInCountry, Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityLocatedInCountry Context triple: [MA, cityLocatedInCountry, Germany]
-
A.
cityLocatedIn
chosen
Indicates that a city is geographically situated within a specified larger administrative or territorial region.
-
B.
countryLocated
Indicates that a country is geographically situated within or associated with a specific larger region, territory, or political entity.
-
C.
locatedInCountryCapitalOfProvince
Indicates that an entity is located in the country that contains the capital city of a specified province.
-
D.
countryCapitalOfLocatedCity
Indicates that a city serves as the capital of a country and is geographically located within that country.
-
E.
provinceSeatCountry
Indicates that a country serves as the national context or sovereign state for the seat (capital/administrative center) of a given province.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293457120819098af138fdd01846d |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:59 a.m.