Triple
T21213535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LAN Argentina |
E522777
|
entity |
| Predicate | focusCity |
P164
|
FINISHED |
| Object | Salta |
—
|
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: Salta | Statement: [LAN Argentina, focusCity, Salta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salta Context triple: [LAN Argentina, focusCity, Salta]
-
A.
Salta (city)
chosen
Salta is a historic city in northwestern Argentina known for its well-preserved colonial architecture, vibrant cultural traditions, and role as a regional commercial and tourism hub in the Lerma Valley.
-
B.
Salta Province
Salta Province is a large, landlocked region in northwestern Argentina known for its colonial architecture, Andean landscapes, and significant agricultural and wine production.
-
C.
Belén
Belén is a town in northwestern Argentina known for its traditional weaving and role as a regional center in Catamarca Province.
-
D.
Belén
Belén is a municipality located in the Rivas Department of southwestern Nicaragua, known for its rural character and agricultural activities.
-
E.
Belén
Belén is a common Spanish feminine given name, often used as a diminutive of "Belén María" and associated with the Spanish word for Bethlehem.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7347088488190aa764b3f4bbac44d |
completed | April 21, 2026, 8:25 a.m. |
Created at: April 16, 2026, 3:38 p.m.