Triple
T1346006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sinaloa |
E28571
|
entity |
| Predicate | hasImportantPort |
P6498
|
FINISHED |
| Object |
Topolobampo
Topolobampo is a major Pacific coast port city in northwestern Mexico, serving as an important hub for maritime trade and ferry connections in the state of Sinaloa.
|
E154229
|
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: Topolobampo | Statement: [Sinaloa, hasImportantPort, Topolobampo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Topolobampo Context triple: [Sinaloa, hasImportantPort, Topolobampo]
-
A.
Cholula
Cholula is a historic Mexican city famed for its Great Pyramid and rich pre-Hispanic and colonial heritage.
-
B.
Tejipió
Tejipió is a neighborhood in the city of Recife, Brazil, known as part of the urban fabric of the state capital of Pernambuco.
-
C.
Mexican Cocopa
Mexican Cocopa is a regional variety of the Cocopa language spoken by Cocopa communities in northern Mexico.
-
D.
Samborondón
Samborondón is a rapidly growing, affluent canton and town in coastal Ecuador, located across the river from Guayaquil and known for its upscale residential and commercial developments.
-
E.
Sopó
Sopó is a small municipality in the department of Cundinamarca, Colombia, known for its scenic Andean landscapes and dairy production.
- 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: Topolobampo Triple: [Sinaloa, hasImportantPort, Topolobampo]
Generated description
Topolobampo is a major Pacific coast port city in northwestern Mexico, serving as an important hub for maritime trade and ferry connections in the state of Sinaloa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Topolobampo Target entity description: Topolobampo is a major Pacific coast port city in northwestern Mexico, serving as an important hub for maritime trade and ferry connections in the state of Sinaloa.
-
A.
Cholula
Cholula is a historic Mexican city famed for its Great Pyramid and rich pre-Hispanic and colonial heritage.
-
B.
Tejipió
Tejipió is a neighborhood in the city of Recife, Brazil, known as part of the urban fabric of the state capital of Pernambuco.
-
C.
Mexican Cocopa
Mexican Cocopa is a regional variety of the Cocopa language spoken by Cocopa communities in northern Mexico.
-
D.
Samborondón
Samborondón is a rapidly growing, affluent canton and town in coastal Ecuador, located across the river from Guayaquil and known for its upscale residential and commercial developments.
-
E.
Sopó
Sopó is a small municipality in the department of Cundinamarca, Colombia, known for its scenic Andean landscapes and dairy production.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23e84188190b0395c57dd45b62a |
completed | March 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc639201c81908ed9c9ac37cd358f |
completed | March 8, 2026, 12:43 a.m. |
| NEDg | Description generation | batch_69acc71a3e808190aecbb57a64f39b6b |
completed | March 8, 2026, 12:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acc88e4ec08190945b366524b83088 |
completed | March 8, 2026, 12:53 a.m. |
Created at: March 1, 2026, 7:56 p.m.