Triple
T19381260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peruvian Andes |
E484815
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Misti |
—
|
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: Misti | Statement: [Peruvian Andes, contains, Misti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Misti Context triple: [Peruvian Andes, contains, Misti]
-
A.
Misti
chosen
Misti is a prominent, snow-capped stratovolcano overlooking the city of Arequipa in southern Peru.
-
B.
Missy
Missy is the female incarnation of the Master, a recurring Time Lord villain and nemesis of the Doctor in the British science fiction series Doctor Who.
-
C.
Missy
Missy is a small Swiss municipality located in the canton of Vaud.
-
D.
Missy
Missy is the affectionate nickname of Queen Marie of Romania, the influential early 20th-century queen consort known for her political influence, diplomacy, and cultural impact in Romania.
-
E.
Mimi
Mimi is a common affectionate diminutive or nickname for the given name Marie.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a6075a88190aed7afa3b8fd3021 |
completed | April 20, 2026, 12:21 p.m. |
Created at: April 10, 2026, 1:35 p.m.