Triple
T24973630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USGS Franconia |
E624957
|
entity |
| Predicate | coversPeak |
P53629
|
FINISHED |
| Object | Mount Lafayette |
—
|
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: Mount Lafayette | Statement: [USGS Franconia, coversPeak, Mount Lafayette]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversPeak Context triple: [USGS Franconia, coversPeak, Mount Lafayette]
-
A.
includesPeak
chosen
Indicates that one entity contains or encompasses a highest point, maximum value, or peak within its scope or range.
-
B.
areaPeak
Indicates that a specified location or region is the highest point (peak) within a given area or spatial extent.
-
C.
depictsPeak
Indicates that one entity visually represents or portrays the highest or most intense point of another entity or process.
-
D.
hasHighestPeaksOver
Indicates that one entity possesses mountain peaks that are higher in elevation than those of another entity.
-
E.
isEasternPeakOf
Indicates that one peak is the eastern member or counterpart within a set or pair of related peaks.
- F. None of above.
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_69e2ff24512481908e9a72315b8d0354 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 6:01 a.m.