Triple
T4218626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sal |
E94282
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Santa Maria
Santa Maria is a coastal town on the southern tip of Sal Island in Cape Verde, known for its sandy beaches, tourism, and water sports.
|
E424202
|
NE FINISHED |
How this triple was built (4 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 | Statement: [Sal, hasTown, Santa Maria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Maria Context triple: [Sal, hasTown, Santa Maria]
-
A.
Santa Maria
Santa Maria is a city in California’s Central Coast region known for its agriculture, wine industry, and distinctive Santa Maria–style barbecue.
-
B.
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.
-
C.
Santa Maria
Santa Maria is a first-class, landlocked municipality in the province of Bulacan in the Philippines, known for its rapidly growing suburban communities and proximity to Metro Manila.
-
D.
Santa María
Santa María was the largest of the three ships used by Christopher Columbus on his first voyage across the Atlantic in 1492.
-
E.
Santa María
Santa María is a town in northwestern Argentina known as an agricultural and archaeological center in the Calchaquí Valley region of Catamarca Province.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Santa Maria Triple: [Sal, hasTown, Santa Maria]
Generated description
Santa Maria is a coastal town on the southern tip of Sal Island in Cape Verde, known for its sandy beaches, tourism, and water sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Maria Target entity description: Santa Maria is a coastal town on the southern tip of Sal Island in Cape Verde, known for its sandy beaches, tourism, and water sports.
-
A.
Santa Maria
Santa Maria is a city in California’s Central Coast region known for its agriculture, wine industry, and distinctive Santa Maria–style barbecue.
-
B.
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.
-
C.
Santa Maria
Santa Maria is a first-class, landlocked municipality in the province of Bulacan in the Philippines, known for its rapidly growing suburban communities and proximity to Metro Manila.
-
D.
Santa María
Santa María was the largest of the three ships used by Christopher Columbus on his first voyage across the Atlantic in 1492.
-
E.
Santa María
Santa María is a small Chilean city and commune located in the Valparaíso Region, known for its agricultural activity within the Aconcagua Valley.
- F. None of above. chosen
Provenance (5 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5a858a5b08190990a896265ac9725 |
completed | March 14, 2026, 6:26 p.m. |
| NEDg | Description generation | batch_69b5ac2e0824819084f02a8be9019764 |
completed | March 14, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5ac9843fc8190bb4284b4e66abee5 |
completed | March 14, 2026, 6:44 p.m. |
Created at: March 12, 2026, 11:04 p.m.