Triple
T7268308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cala Millor |
E161034
|
entity |
| Predicate | hasNearbyLocality |
P3883
|
FINISHED |
| Object |
Sa Coma
Sa Coma is a coastal resort town on the eastern coast of Mallorca, Spain, known for its sandy beach and tourist amenities.
|
E652911
|
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: Sa Coma | Statement: [Cala Millor, hasNearbyLocality, Sa Coma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sa Coma Context triple: [Cala Millor, hasNearbyLocality, Sa Coma]
-
A.
Ascó
Ascó is a municipality in Catalonia, Spain, best known for hosting one of the country’s major nuclear power plants along the Ebro River.
-
B.
Somosta
Somosta is a town located within Egypt's Beni Suef Governorate, known as one of the local urban centers in this Upper Egyptian region.
-
C.
Jauja
Jauja is a historic highland city in central Peru, known as the country’s first Spanish-founded capital and for its colonial architecture and Andean cultural heritage.
-
D.
Santena
Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
-
E.
San Gil
San Gil is a popular Colombian town in the Santander Department known as an adventure tourism hub for activities like rafting, caving, and paragliding.
- 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: Sa Coma Triple: [Cala Millor, hasNearbyLocality, Sa Coma]
Generated description
Sa Coma is a coastal resort town on the eastern coast of Mallorca, Spain, known for its sandy beach and tourist amenities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sa Coma Target entity description: Sa Coma is a coastal resort town on the eastern coast of Mallorca, Spain, known for its sandy beach and tourist amenities.
-
A.
Ascó
Ascó is a municipality in Catalonia, Spain, best known for hosting one of the country’s major nuclear power plants along the Ebro River.
-
B.
Somosta
Somosta is a town located within Egypt's Beni Suef Governorate, known as one of the local urban centers in this Upper Egyptian region.
-
C.
Jauja
Jauja is a historic highland city in central Peru, known as the country’s first Spanish-founded capital and for its colonial architecture and Andean cultural heritage.
-
D.
Santena
Santena is a small town in the Piedmont region of northern Italy, known for its historical association with statesman Camillo Benso, Count of Cavour.
-
E.
San Gil
San Gil is a popular Colombian town in the Santander Department known as an adventure tourism hub for activities like rafting, caving, and paragliding.
- 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eae8cc288190bc3ae3c7b38980d0 |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db1e4f9c8190a23ce5a35073b7c7 |
completed | March 28, 2026, 1:43 p.m. |
| NEDg | Description generation | batch_69c7dbd350a08190aa34ada9ba8d39ce |
completed | March 28, 2026, 1:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7dc7cb2d48190a40523eb7b03a9ef |
completed | March 28, 2026, 1:49 p.m. |
Created at: March 27, 2026, 2:58 p.m.