Triple
T1417042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Western Divide |
E31940
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Mount Lawson
Mount Lawson is a peak in California’s Sierra Nevada range, situated along the rugged Great Western Divide within Sequoia National Park.
|
E161397
|
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: Mount Lawson | Statement: [Great Western Divide, contains, Mount Lawson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mount Lawson Context triple: [Great Western Divide, contains, Mount Lawson]
-
A.
Telegraph Hill
Telegraph Hill is a historic San Francisco neighborhood and prominent hill known for its sweeping bay views, steep stairways, and flocks of wild parrots.
-
B.
Science Hill
Science Hill is a major academic area of Yale University that houses many of the university’s science departments, laboratories, and research facilities.
-
C.
Mount Catherine
Mount Catherine is the highest mountain in Egypt, located in the southern Sinai Peninsula and known for its rugged terrain and religious significance.
-
D.
Mount Hollywood
Mount Hollywood is a prominent peak in Los Angeles’ Griffith Park offering panoramic views of the city and the surrounding hills.
-
E.
Brewster Hill
Brewster Hill is a small residential hamlet within the Town of Southeast in Putnam County, New York.
- 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: Mount Lawson Triple: [Great Western Divide, contains, Mount Lawson]
Generated description
Mount Lawson is a peak in California’s Sierra Nevada range, situated along the rugged Great Western Divide within Sequoia National Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mount Lawson Target entity description: Mount Lawson is a peak in California’s Sierra Nevada range, situated along the rugged Great Western Divide within Sequoia National Park.
-
A.
Telegraph Hill
Telegraph Hill is a historic San Francisco neighborhood and prominent hill known for its sweeping bay views, steep stairways, and flocks of wild parrots.
-
B.
Science Hill
Science Hill is a major academic area of Yale University that houses many of the university’s science departments, laboratories, and research facilities.
-
C.
Mount Catherine
Mount Catherine is the highest mountain in Egypt, located in the southern Sinai Peninsula and known for its rugged terrain and religious significance.
-
D.
Mount Hollywood
Mount Hollywood is a prominent peak in Los Angeles’ Griffith Park offering panoramic views of the city and the surrounding hills.
-
E.
Brewster Hill
Brewster Hill is a small residential hamlet within the Town of Southeast in Putnam County, New York.
- 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_69a49919a994819086528951bc224775 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c403ccdc8190b2a5fda037b6ea34 |
completed | March 1, 2026, 10:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ace5833bb88190bcaf8cf46264ab26 |
completed | March 8, 2026, 2:57 a.m. |
| NEDg | Description generation | batch_69ace61d60d48190a72aaa68264997eb |
completed | March 8, 2026, 2:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ace6d8e35c8190bff4beff48977efc |
completed | March 8, 2026, 3:02 a.m. |
Created at: March 1, 2026, 7:59 p.m.