Triple
T13751848
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMARTS 1.0m Telescope |
E330371
|
entity |
| Predicate | locatedNearCity |
P3883
|
FINISHED |
| Object | La Serena |
E503
|
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: La Serena | Statement: [SMARTS 1.0m Telescope, locatedNearCity, La Serena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Serena Context triple: [SMARTS 1.0m Telescope, locatedNearCity, La Serena]
-
A.
La Serena
chosen
La Serena is a coastal city in northern Chile known for its colonial architecture, beaches, and role as a gateway to major astronomical observatories in the region.
-
B.
Vallenar
Vallenar is a city in northern Chile known as an agricultural and mining center in the Atacama Desert.
-
C.
Maipú
Maipú is a renowned wine-producing region in Argentina’s Mendoza Province, noted for its high-quality Malbec and other varietals.
-
D.
Maipú
Maipú is a populous commune and suburb of Santiago, Chile, known for its residential areas, commercial activity, and historical significance in the Santiago Metropolitan Region.
-
E.
Valparaíso
Valparaíso is a rural municipality located in the Caquetá Department of southern Colombia, known for its Amazonian landscapes and agricultural economy.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0d591648190beb4430c6b199eb8 |
completed | May 3, 2026, 9:40 p.m. |
Created at: April 9, 2026, 10:09 p.m.