Triple
T14607807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiflón del Diablo mine |
E342877
|
entity |
| Predicate | locatedIn |
P40
|
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: [Chiflón del Diablo mine, locatedIn, Lota]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lota Context triple: [Chiflón del Diablo mine, locatedIn, 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.
Chamkani
Chamkani is a Pashtun tribe traditionally associated with the Karlani tribal confederation in the Afghanistan–Pakistan border region.
-
D.
Kalsa
Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
-
E.
Salar
Salar is a Turkic ethnic group primarily residing in northwestern China, known for speaking the Salar language and practicing Islam.
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb44d327c8190a8d20568429d0f80 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94d09e988190a2a2a1332397b412 |
completed | May 8, 2026, 7:46 a.m. |
Created at: April 10, 2026, 1:25 a.m.