Triple
T15723757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marinha Grande |
E381168
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Leiria |
—
|
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: Leiria | Statement: [Marinha Grande, hasNearbyCity, Leiria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Leiria Context triple: [Marinha Grande, hasNearbyCity, Leiria]
-
A.
Leiria
chosen
Leiria is a historic city in central Portugal known for its medieval hilltop castle and role as a regional administrative and cultural center.
-
B.
Alcobaça
Alcobaça is a historic Portuguese city best known for its UNESCO-listed Cistercian monastery, one of the country’s most important medieval monuments.
-
C.
Lousã
Lousã is a town and municipality in central Portugal known for its surrounding mountains, schist villages, and outdoor activities such as hiking and mountain biking.
-
D.
Lourinhã
Lourinhã is a coastal municipality in western Portugal known for its rich dinosaur fossil discoveries and scenic Atlantic beaches.
-
E.
Caldas da Rainha
Caldas da Rainha is a historic spa and market city in western Portugal, renowned for its thermal baths, ceramics tradition, and proximity to the Atlantic coast.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb1fdd4819088f3e243263e5f73 |
completed | April 16, 2026, 2:55 a.m. |
Created at: April 10, 2026, 4:46 a.m.