Triple
T4743830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cardenal Caro Province |
E105312
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pichilemu |
E504201
|
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: Pichilemu | Statement: [Cardenal Caro Province, contains, Pichilemu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pichilemu Context triple: [Cardenal Caro Province, contains, Pichilemu]
-
A.
Pichilemu
chosen
Pichilemu is a coastal Chilean city renowned as a major surfing destination and seaside resort on the Pacific Ocean.
-
B.
Puerto Varas
Puerto Varas is a picturesque lakeside city in southern Chile’s Los Lagos Region, known for its German-influenced architecture and views of the Osorno and Calbuco volcanoes.
-
C.
Talcahuano
Talcahuano is a major Chilean port city and naval base known for its shipyards and fishing industry.
-
D.
Vallenar
Vallenar is a city in northern Chile known as an agricultural and mining center in the Atacama Desert.
-
E.
Puerto Aysén
Puerto Aysén is a small port city in Chilean Patagonia that serves as a key gateway to the fjords, glaciers, and national parks of the Aysén Region.
- 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_69bd43ef87a48190a5bc3600711aa032 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64a85e9c81908e9c7bbbb998953e |
completed | March 20, 2026, 3:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe41822c8190b406c192170af3d1 |
completed | March 21, 2026, 8:23 p.m. |
Created at: March 20, 2026, 1:19 p.m.