Triple
T12329775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iglesia de Nuestra Señora de Belén |
E293926
|
entity |
| Predicate | isLandmarkOf |
P6629
|
FINISHED |
| Object | Belén |
E60654
|
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: Belén | Statement: [Iglesia de Nuestra Señora de Belén, isLandmarkOf, Belén]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Belén Context triple: [Iglesia de Nuestra Señora de Belén, isLandmarkOf, Belén]
-
A.
Belén
chosen
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
B.
Belen
Belen is a small city in central New Mexico known as a regional transportation hub and bedroom community for the Albuquerque metropolitan area.
-
C.
Malasaña
Malasaña is a vibrant central Madrid neighborhood known for its bohemian atmosphere, nightlife, and alternative cultural scene.
-
D.
Colomars
Colomars is a small commune in southeastern France situated in the hills northwest of Nice, known for its scenic Mediterranean landscape and proximity to the French Riviera.
-
E.
San Miguel de Lillo
San Miguel de Lillo is a 9th-century pre-Romanesque church near Oviedo in Asturias, Spain, renowned for its distinctive Asturian architecture and UNESCO World Heritage status.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62aa12f108190851c6958eb35ee5b |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.