Triple
T20740784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | México 1 |
E510433
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Ensenada |
—
|
NE NERFINISHED |
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: Ensenada | Statement: [México 1, passesThrough, Ensenada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ensenada Context triple: [México 1, passesThrough, Ensenada]
-
A.
Ensenada
Ensenada is a small lakeside village in southern Chile’s Los Lagos Region, known as a gateway to outdoor activities around Lake Llanquihue and the nearby Osorno Volcano.
-
B.
Ensenada
Ensenada is a coastal municipality in Buenos Aires Province, Argentina, known for its port, industrial activity, and proximity to the city of La Plata.
-
C.
Ensenada
chosen
Ensenada is a coastal city in northwestern Baja California, Mexico, known for its busy port, tourism, and nearby wine-producing valleys.
-
D.
Guadalimar
Guadalimar is a river in southern Spain that flows through the Province of Jaén as a tributary of the Guadalquivir.
-
E.
Tijuana
Tijuana is a large, bustling border city in northwestern Mexico known for its cultural vibrancy, manufacturing industry, and close economic and social ties with the neighboring U.S. city of San Diego.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c845e88190b4c5f3ae79291182 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c20e76ac8190985203b2c17aca14 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:32 p.m.