Triple
T22861589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Felix Pappalardi |
E566935
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | 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: Mountain | Statement: [Felix Pappalardi, associatedAct, Mountain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mountain Context triple: [Felix Pappalardi, associatedAct, Mountain]
-
A.
Mountain
Mountain is the nickname of Harlan "Mountain" McClintock, a character from the television series The Twilight Zone.
-
B.
Mountain
chosen
Mountain is an American hard rock band, best known for their heavy blues-influenced sound and the classic rock hit "Mississippi Queen."
-
C.
Mount
Mount is the surname of American actor Anson Mount, known for his roles in television series such as "Hell on Wheels" and "Star Trek: Discovery."
-
D.
Montagne
Montagne was a prominent French ship of the line that served as the flagship of the French fleet during the late 18th century.
-
E.
Mount Scenery
Mount Scenery is a dormant volcano and the highest peak in the Kingdom of the Netherlands, located on the Caribbean island of Saba.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17efcc1308190a95d10e431295ca2 |
completed | April 29, 2026, 3:46 a.m. |
Created at: April 17, 2026, 3:37 p.m.