Triple
T1001054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moshe Cordovero |
E21602
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Tomer Devorah
Tomer Devorah is a seminal Kabbalistic ethical treatise by Rabbi Moshe Cordovero that guides readers in imitating the divine attributes of mercy and compassion.
|
E118817
|
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: Tomer Devorah | Statement: [Moshe Cordovero, notableWork, Tomer Devorah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tomer Devorah Context triple: [Moshe Cordovero, notableWork, Tomer Devorah]
-
A.
Ayelet Zurer
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
-
B.
Ze'ev
Ze'ev is a Hebrew given name meaning "wolf," commonly used in Israel and among Jewish communities worldwide.
-
C.
Haviv Ilan
Haviv Ilan is a business executive who leads the global semiconductor company Texas Instruments as its chief executive officer.
-
D.
Tamara Geva
Tamara Geva was a Russian-American dancer and actress known for her early collaborations with choreographer George Balanchine and her influential work on Broadway and in modern ballet.
-
E.
Orly Sud
Orly Sud is the former name of Orly 4, a terminal facility at Paris Orly Airport in France.
- 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: Tomer Devorah Triple: [Moshe Cordovero, notableWork, Tomer Devorah]
Generated description
Tomer Devorah is a seminal Kabbalistic ethical treatise by Rabbi Moshe Cordovero that guides readers in imitating the divine attributes of mercy and compassion.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tomer Devorah Target entity description: Tomer Devorah is a seminal Kabbalistic ethical treatise by Rabbi Moshe Cordovero that guides readers in imitating the divine attributes of mercy and compassion.
-
A.
Ayelet Zurer
Ayelet Zurer is an Israeli actress known internationally for her roles in films such as "Angels & Demons," "Munich," and "Man of Steel."
-
B.
Ze'ev
Ze'ev is a Hebrew given name meaning "wolf," commonly used in Israel and among Jewish communities worldwide.
-
C.
Haviv Ilan
Haviv Ilan is a business executive who leads the global semiconductor company Texas Instruments as its chief executive officer.
-
D.
Tamara Geva
Tamara Geva was a Russian-American dancer and actress known for her early collaborations with choreographer George Balanchine and her influential work on Broadway and in modern ballet.
-
E.
Orly Sud
Orly Sud is the former name of Orly 4, a terminal facility at Paris Orly Airport in France.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a1cb4f08190b1351aadd57c3bda |
completed | March 7, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_69ac2b0d1b348190b4a34bf1c9b43968 |
completed | March 7, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ac2bb03508819095f791903f048351 |
completed | March 7, 2026, 1:44 p.m. |
Created at: March 1, 2026, 7:41 p.m.