Triple
T16359185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deuteronomy 34 |
E397265
|
entity |
| Predicate | mainCharacter |
P1183
|
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: [Deuteronomy 34, mainCharacter, Moses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Moses Context triple: [Deuteronomy 34, mainCharacter, 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.
Moses
Moses is a narrative poem by Ukrainian writer Ivan Franko that reinterprets the biblical story of the prophet Moses as an allegory for the Ukrainian people's struggle and destiny.
-
C.
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.
-
D.
Moshe
Moshe is the Hebrew given name of the influential 16th-century Polish rabbi and halachic authority known as the Rema of Kraków (Rabbi Moses Isserles).
-
E.
Mūsa
Mūsa is a river in Latvia that serves as one of the main tributaries forming the larger Lielupe River.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2fad1859c819082b47bf9d7fabd9f |
completed | April 18, 2026, 3:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dbce2508190b655de87f48e841e |
completed | May 10, 2026, 7:03 a.m. |
Created at: April 10, 2026, 5:07 a.m.