Triple
T11663437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fiscal |
E277182
|
entity |
| Predicate | municipality |
P852
|
FINISHED |
| Object | Amares |
E716729
|
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: Amares | Statement: [Fiscal, municipality, Amares]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amares Context triple: [Fiscal, municipality, Amares]
-
A.
Amares
chosen
Amares is a municipality in northern Portugal known for its rural landscapes, historical churches, and proximity to the city of Braga in the Minho region.
-
B.
Amar'e
Amar'e is a retired American professional basketball player best known as an explosive All-Star power forward in the NBA, primarily with the Phoenix Suns and New York Knicks.
-
C.
Amarar
Amarar is the native name used by the Beja people to refer to themselves or their community.
-
D.
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.
-
E.
Ameide
Ameide is a small historic town in the Dutch province of South Holland, known for its location along the Lek River and traditional Dutch architecture.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d3a64c819099f398ea22c8c180 |
completed | April 10, 2026, 7:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef13a2f1dc8190bb9ca8879ef42e14 |
completed | April 27, 2026, 7:43 a.m. |
Created at: April 8, 2026, 9:39 p.m.