Triple
T5372769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gran Concepción |
E108889
|
entity |
| Predicate | hasIndustrialCity |
P3436
|
FINISHED |
| Object | Lota |
E68423
|
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: Lota | Statement: [Gran Concepción, hasIndustrialCity, Lota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lota Context triple: [Gran Concepción, hasIndustrialCity, Lota]
-
A.
Lota
chosen
Lota is a coastal city in southern Chile known historically for its coal mining industry and maritime heritage.
-
B.
Salcha
Salcha is a small unincorporated community in interior Alaska, known for its rural setting along the Tanana River southeast of Fairbanks.
-
C.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
D.
Salar
Salar is a Turkic ethnic group primarily residing in northwestern China, known for speaking the Salar language and practicing Islam.
-
E.
Sincholagua
Sincholagua is a stratovolcano in the Ecuadorian Andes, located southeast of Quito and known for its rugged, glaciated peak.
- 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_69bd440c77948190aad2a5f39b7b80f5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd86abc1e88190ad08279c3bf238e5 |
completed | March 20, 2026, 5:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf411955e8819082648e9a86fbaf7c |
completed | March 22, 2026, 1:08 a.m. |
Created at: March 20, 2026, 2:03 p.m.