Triple
T19839775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UMAG |
E476694
|
entity |
| Predicate | regionSpecialization |
P21480
|
FINISHED |
| Object |
Magallanes
Magallanes is the southernmost region of Chile, known for its rugged Patagonian landscapes, subpolar climate, and proximity to Antarctica.
|
E1398645
|
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: Magallanes | Statement: [UMAG, regionSpecialization, Magallanes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magallanes Context triple: [UMAG, regionSpecialization, Magallanes]
-
A.
Magallanes
Magallanes is a Chilean professional football club known for its historic role in the early development of Chilean soccer.
-
B.
Magallanes
Magallanes is a landlocked agricultural municipality in the province of Cavite in the Philippines, known for its rural character and historical roots.
-
C.
Magallanes
Magallanes is a coastal municipality in the province of Agusan del Norte in the Caraga region of Mindanao, Philippines.
-
D.
Villalobón
Villalobón is a small municipality in the autonomous community of Castile and León in northern Spain.
-
E.
Vespucio Sur
Vespucio Sur is a major urban highway in Santiago, Chile, forming part of the city’s beltway system and facilitating high-capacity traffic flow around the southern sector of the capital.
- 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: Magallanes Triple: [UMAG, regionSpecialization, Magallanes]
Generated description
Magallanes is the southernmost region of Chile, known for its rugged Patagonian landscapes, subpolar climate, and proximity to Antarctica.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Magallanes Target entity description: Magallanes is the southernmost region of Chile, known for its rugged Patagonian landscapes, subpolar climate, and proximity to Antarctica.
-
A.
Magallanes
Magallanes is a Chilean professional football club known for its historic role in the early development of Chilean soccer.
-
B.
Magallanes
Magallanes is a landlocked agricultural municipality in the province of Cavite in the Philippines, known for its rural character and historical roots.
-
C.
Magallanes
Magallanes is a coastal municipality in the province of Agusan del Norte in the Caraga region of Mindanao, Philippines.
-
D.
Villalobón
Villalobón is a small municipality in the autonomous community of Castile and León in northern Spain.
-
E.
Vespucio Sur
Vespucio Sur is a major urban highway in Santiago, Chile, forming part of the city’s beltway system and facilitating high-capacity traffic flow around the southern sector of the capital.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65804be608190b49e110c3bf381bc |
completed | April 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07d436990481908bb488d3935fa773 |
completed | May 16, 2026, 2:19 a.m. |
| NEDg | Description generation | batch_6a07d5ec45208190a75365a4a411aa7c |
completed | May 16, 2026, 2:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07d6ffc6508190aa9df66c2cf3d532 |
completed | May 16, 2026, 2:31 a.m. |
Created at: April 10, 2026, 1:50 p.m.