Triple
T10645643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Born |
E250826
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object | Santa Maria del Mar |
E859294
|
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: Santa Maria del Mar | Statement: [El Born, hasLandmark, Santa Maria del Mar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Maria del Mar Context triple: [El Born, hasLandmark, Santa Maria del Mar]
-
A.
Santa Maria del Mar
chosen
Santa Maria del Mar is a renowned 14th-century Catalan Gothic basilica in Barcelona, celebrated for its harmonious architecture and striking stained-glass windows.
-
B.
Santa Maria Maddalena
Santa Maria Maddalena is a Baroque-style Roman Catholic church in central Rome, noted for its ornate Rococo interior and distinctive façade.
-
C.
Santa María la Ribera
Santa María la Ribera is a historic neighborhood in Mexico City known for its late 19th-century architecture, traditional plazas, and cultural landmarks.
-
D.
Santa Maria
Santa Maria is a popular sandy beach on the Greek island of Paros, known for its clear waters, water sports, and lively summer atmosphere.
-
E.
Santa Maria
Santa Maria is a major city in southern Brazil known as an educational and military center in the state of Rio Grande do Sul.
- 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_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dfe120908190ab91c38d57133739 |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a580d388190aea5edadd4afc0d1 |
completed | April 10, 2026, 10:31 p.m. |
Created at: April 8, 2026, 9:05 p.m.