Triple
T16103148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferrocarril Central Andino |
E390672
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | La Oroya |
E414879
|
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 Oroya | Statement: [Ferrocarril Central Andino, terminus, La Oroya]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Oroya Context triple: [Ferrocarril Central Andino, terminus, La Oroya]
-
A.
La Oroya
chosen
La Oroya is a Peruvian mining city in the central Andes, historically known for its large metallurgical complex and severe environmental pollution.
-
B.
Guareña
Guareña is a municipality in western Spain’s Extremadura region, known for its agricultural economy and traditional rural character within the Province of Badajoz.
-
C.
Oroquieta
Oroquieta is a coastal city in the Philippines that serves as the capital of Misamis Occidental province on the island of Mindanao.
-
D.
Ubaque
Ubaque is a municipality in central Colombia known for its rural Andean landscapes and traditional agricultural communities.
-
E.
Yajalón
Yajalón is a town and municipality in the Mexican state of Chiapas, known as an important cultural and population center for the Tzeltal Maya people.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6976ec8190b499e99b196b0285 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeba007c08190bf4d3cf092abc7dd |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 5 a.m.