Triple
T9072695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Port of Guaymas |
E217406
|
entity |
| Predicate | servesCity |
P82
|
FINISHED |
| Object | Guaymas |
E187284
|
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: Guaymas | Statement: [Port of Guaymas, servesCity, Guaymas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guaymas Context triple: [Port of Guaymas, servesCity, Guaymas]
-
A.
Guaymas
chosen
Guaymas is a coastal city and major seaport on the Gulf of California in the Mexican state of Sonora.
-
B.
Puerto Guzmán
Puerto Guzmán is a Colombian town and municipality known as one of the main population centers in the Amazonian region of the Putumayo Department.
-
C.
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.
-
D.
Ensenada
Ensenada is a coastal city in northwestern Baja California, Mexico, known for its busy port, tourism, and nearby wine-producing valleys.
-
E.
Manzanillo
Manzanillo is a major Pacific coastal city in western Mexico known for its busy commercial port and popular beach tourism.
- 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_69ca83d6c14c8190bc056d927f00a2a2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc955ffa04819086be5763133c5067 |
completed | April 1, 2026, 3:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d017aea1e481909f329ff451ed941c |
completed | April 3, 2026, 7:40 p.m. |
Created at: March 30, 2026, 7:12 p.m.