Triple
T4226828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Nebo |
E94478
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Moses |
E11297
|
NE FINISHED |
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: Moses | Statement: [Mount Nebo, associatedWith, Moses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moses Context triple: [Mount Nebo, associatedWith, Moses]
-
A.
Moses
chosen
Moses is a central prophet and leader in the Hebrew Bible, traditionally credited with leading the Israelites out of Egypt and receiving the Ten Commandments from God.
-
B.
Mose
Mose is a minor character in Harriet Beecher Stowe’s novel "Uncle Tom’s Cabin," depicted as one of Uncle Tom’s children within the enslaved family central to the story.
-
C.
Moses the Black
Moses the Black was a 4th-century Ethiopian desert monk and former bandit who became a renowned Christian ascetic and saint among the Desert Fathers.
-
D.
Yoshua
Yoshua is a male given name most notably borne by Yoshua Bengio, a pioneering Canadian computer scientist and deep learning researcher.
-
E.
Matan Torah
Matan Torah is the Jewish term for the divine giving of the Torah to the Israelites, traditionally understood to have occurred at Mount Sinai.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e4ed34c819081d1479ce87cd78c |
completed | March 12, 2026, 11:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5964a388881908038e5a612424b9b |
completed | March 14, 2026, 5:09 p.m. |
Created at: March 12, 2026, 11:04 p.m.