Triple
T1931277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulf of California |
E40951
|
entity |
| Predicate | hasCityOnCoast |
P969
|
FINISHED |
| Object | Topolobampo |
E154229
|
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: Topolobampo | Statement: [Gulf of California, hasCityOnCoast, Topolobampo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Topolobampo Context triple: [Gulf of California, hasCityOnCoast, Topolobampo]
-
A.
Topolobampo
chosen
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.
-
B.
Zapote
Zapote is a district of San José, Costa Rica, known for housing important government buildings and urban residential areas.
-
C.
Cholula
Cholula is a historic Mexican city famed for its Great Pyramid and rich pre-Hispanic and colonial heritage.
-
D.
Tejipió
Tejipió is a neighborhood in the city of Recife, Brazil, known as part of the urban fabric of the state capital of Pernambuco.
-
E.
Mexican Cocopa
Mexican Cocopa is a regional variety of the Cocopa language spoken by Cocopa communities in northern Mexico.
- 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_69a8864711648190b07bed24ed76258e |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb296910481908c9668518c09fdb0 |
completed | March 7, 2026, 5:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3ef29e0819081b37664224dee91 |
completed | March 8, 2026, 10:10 p.m. |
Created at: March 4, 2026, 7:35 p.m.