Triple
T8194587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Putaendo |
E191395
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | San Felipe |
E79916
|
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: San Felipe | Statement: [Putaendo, nearbyCity, San Felipe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Felipe Context triple: [Putaendo, nearbyCity, San Felipe]
-
A.
San Felipe
chosen
San Felipe is a historic city in central Chile known for its agricultural surroundings and role as a commercial and administrative center in the Aconcagua Valley.
-
B.
San Felipe
San Felipe is a coastal town in Baja California, Mexico, known as a gateway to nearby natural attractions and desert and mountain landscapes.
-
C.
San Felipe
San Felipe is a small coastal town in Mexico’s Yucatán Peninsula known for its colorful wooden houses, fishing traditions, and access to rich mangrove and wildlife areas.
-
D.
San Felipe
San Felipe is the historic colonial district of Panama City, Panama, known for its preserved architecture, plazas, and cultural landmarks.
-
E.
San Felipe
San Felipe is a coastal municipality in the province of Zambales in the Philippines, known for its surfing beaches and laid-back rural atmosphere.
- 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_69ca82c6e9548190a4c5ca14516e4417 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c1f02248190adbe56a7d6be3419 |
completed | March 31, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedaab8848190877fbe2de9b83957 |
completed | April 1, 2026, 10:04 a.m. |
Created at: March 30, 2026, 5:42 p.m.