Triple
T17617064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanga Parbat |
E429110
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object | Killer Mountain |
—
|
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: Killer Mountain | Statement: [Nanga Parbat, nickname, Killer Mountain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Killer Mountain Context triple: [Nanga Parbat, nickname, Killer Mountain]
-
A.
Killer Mountain
chosen
Killer Mountain is the ominous nickname of Nanga Parbat, a notoriously deadly Himalayan peak in Pakistan’s Diamer District.
-
B.
Wrong Mountain
Wrong Mountain is a stage play best known for featuring actor Ron Rifkin in a prominent theatrical role.
-
C.
Calamity Mountain
Calamity Mountain is a prominent, ominous peak known for its harsh terrain and association with the surrounding Flowed Lands.
-
D.
Bloody Hill
Bloody Hill is the central, blood-soaked ridge in Missouri that served as the main Union defensive position and focal point of fighting during the American Civil War’s Battle of Wilson’s Creek.
-
E.
La Montaña
La Montaña is the traditional mountainous inland region of Cantabria in northern Spain, known for its rugged landscapes, rural villages, and strong cultural identity.
- 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_69d889e1c6148190ba76241e74688f8b |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46d33a2b081908deecee773c333af |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 5:51 a.m.