Triple
T22470627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A11 motorway (Portugal) |
E555486
|
entity |
| Predicate | regionServed |
P82
|
FINISHED |
| Object | Minho |
—
|
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: Minho | Statement: [A11 motorway (Portugal), regionServed, Minho]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Minho Context triple: [A11 motorway (Portugal), regionServed, Minho]
-
A.
Minho
chosen
Minho is a lush, green region in northwest Portugal known for its cool, rainy climate, historic towns, and production of the light, crisp Vinho Verde wines.
-
B.
Minho
Minho is a key protagonist in The Maze Runner series, known as the brave and resourceful Keeper of the Runners who helps lead the Gladers through the deadly maze.
-
C.
Seonghwan
Seonghwan is a locality in South Korea historically noted as the site of the Battle of Seonghwan during the First Sino-Japanese War.
-
D.
Seonghwa
Seonghwa was the era name used during the reign of King Seongjong of the Joseon dynasty in Korea, marking a specific period of his rule.
-
E.
Seong
Seong is a Korean family name shared by various individuals in Korea and the Korean diaspora.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15bdf6dfc8190aa8dc80ad92a9267 |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.