Triple
T6430236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sagarmatha |
E128159
|
entity |
| Predicate | hasFeature |
P182
|
FINISHED |
| Object |
SouthCol
South Col is the high-altitude mountain pass between Mount Everest and Lhotse that serves as the final major campsite for climbers attempting Everest’s summit via the southeast ridge.
|
E591781
|
NE FINISHED |
How this triple was built (4 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: SouthCol | Statement: [Sagarmatha, hasFeature, SouthCol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SouthCol Context triple: [Sagarmatha, hasFeature, SouthCol]
-
A.
Zuidland
Zuidland is a village in the western Netherlands, located in the province of South Holland.
-
B.
Costa Sur
Costa Sur is a coastal region in the Mexican state of Jalisco known for its Pacific beaches, fishing villages, and tourism.
-
C.
Argentaria
Argentaria was a Spanish state-owned banking group that later merged into what is now Banco Bilbao Vizcaya Argentaria (BBVA).
-
D.
southern Australia
Southern Australia is a temperate region of the Australian continent characterized by diverse ecosystems ranging from coastal areas and woodlands to semi-arid inland habitats.
-
E.
Melena del Sur
Melena del Sur is a coastal municipality in western Cuba known for its agricultural activities and proximity to Havana.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: SouthCol Triple: [Sagarmatha, hasFeature, SouthCol]
Generated description
South Col is the high-altitude mountain pass between Mount Everest and Lhotse that serves as the final major campsite for climbers attempting Everest’s summit via the southeast ridge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SouthCol Target entity description: South Col is the high-altitude mountain pass between Mount Everest and Lhotse that serves as the final major campsite for climbers attempting Everest’s summit via the southeast ridge.
-
A.
Zuidland
Zuidland is a village in the western Netherlands, located in the province of South Holland.
-
B.
Costa Sur
Costa Sur is a coastal region in the Mexican state of Jalisco known for its Pacific beaches, fishing villages, and tourism.
-
C.
Argentaria
Argentaria was a Spanish state-owned banking group that later merged into what is now Banco Bilbao Vizcaya Argentaria (BBVA).
-
D.
southern Australia
Southern Australia is a temperate region of the Australian continent characterized by diverse ecosystems ranging from coastal areas and woodlands to semi-arid inland habitats.
-
E.
Melena del Sur
Melena del Sur is a coastal municipality in western Cuba known for its agricultural activities and proximity to Havana.
- F. None of above. chosen
Provenance (5 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0693b872c819082a7d0e257018831 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c640e9ae8481909229bcf6d5e793d3 |
completed | March 27, 2026, 8:33 a.m. |
| NEDg | Description generation | batch_69c641ff05c08190ab9526b095b038fa |
completed | March 27, 2026, 8:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c642a344e48190bccb0f0d122fca4c |
completed | March 27, 2026, 8:41 a.m. |
Created at: March 22, 2026, 4:44 p.m.