Triple
T1309260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blessing of Moses |
E27950
|
entity |
| Predicate | addressesTribe |
P265
|
FINISHED |
| Object | Levi |
E64668
|
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: Levi | Statement: [Blessing of Moses, addressesTribe, Levi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Levi Context triple: [Blessing of Moses, addressesTribe, Levi]
-
A.
Levi
Levi is the surname of Primo Levi, the renowned Italian Jewish chemist and writer best known for his memoirs about surviving the Auschwitz concentration camp.
-
B.
Levi
chosen
Levi is a biblical patriarch, one of the twelve sons of Jacob and ancestor of the Israelite tribe of Levi, traditionally associated with priestly duties.
-
C.
Levi's
Levi's is an iconic American denim and apparel brand best known for pioneering blue jeans and casual wear worldwide.
-
D.
Barron
Barron is the youngest son of former U.S. President Donald Trump and former First Lady Melania Trump.
-
E.
Lev
Lev is the Russian given name of the renowned writer Leo Tolstoy, under which he was known in his native language.
- 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_69a496d7d83481908f83085854e51328 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c48d25608190b069fb4d0d460aa6 |
completed | March 1, 2026, 10:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acb30b45708190aaf8c977fef2500c |
completed | March 7, 2026, 11:21 p.m. |
Created at: March 1, 2026, 7:51 p.m.