Triple
T8950755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sankt Vith canton |
E213339
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Amel |
E192746
|
NE 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: Amel | Statement: [Sankt Vith canton, contains, Amel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amel Context triple: [Sankt Vith canton, contains, Amel]
-
A.
Amel
chosen
Amel is a municipality in the predominantly German-speaking region of eastern Belgium, known for its rural character and location in the Ardennes.
-
B.
Amreya
Amreya is a district within Egypt’s Alexandria region, known for its mix of industrial zones, residential areas, and proximity to the Mediterranean coast.
-
C.
Amee
Amee is a character portrayed by Katie Lucas, likely within a film or television production.
-
D.
Amed
Amed is a coastal fishing village and popular diving and snorkeling destination in eastern Bali, Indonesia, known for its black sand beaches and coral reefs.
-
E.
Amed
Amed is the historical name of the city now known as Diyarbakır, a major cultural and political center in southeastern Turkey, especially significant for Kurdish heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670c7244819084978922a9835bc9 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc20a5ab481909e10f3abf679ec4c |
completed | April 3, 2026, 1:35 p.m. |
Created at: March 30, 2026, 6:59 p.m.