Triple
T18986026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mafra National Palace |
E464560
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Mafra |
—
|
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: Mafra | Statement: [Mafra National Palace, locatedIn, Mafra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mafra Context triple: [Mafra National Palace, locatedIn, Mafra]
-
A.
Mafra
chosen
Mafra is a Portuguese town best known for its monumental baroque National Palace and basilica, extensively built using local lioz limestone.
-
B.
Nova Sintra
Nova Sintra is the main town and administrative center of the island of Brava in Cape Verde, known for its colonial architecture and mountainous setting.
-
C.
Mafra National Palace
Mafra National Palace is a vast Baroque royal complex in Mafra, Portugal, renowned for its grand basilica, monumental convent, and one of Europe’s most important historic libraries.
-
D.
Sintra
Sintra is a historic Portuguese town near Lisbon, renowned for its romantic 19th-century palaces, castles, and lush hillside landscapes.
-
E.
Vila Real
Vila Real is a historic city in northern Portugal known for its scenic Douro Valley surroundings and notable Baroque architecture.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65f7f08819088f56e8e030851b1 |
completed | April 20, 2026, 7:31 a.m. |
Created at: April 10, 2026, 12:01 p.m.