Triple
T3098990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levi |
E64668
|
entity |
| Predicate | descendant |
P5206
|
FINISHED |
| Object | Gershon |
E307998
|
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: Gershon | Statement: [Levi, descendant, Gershon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gershon Context triple: [Levi, descendant, Gershon]
-
A.
Gershon
chosen
Gershon is the surname of American actress Gina Gershon, known for her roles in films like "Showgirls" and "Bound."
-
B.
Meir
Meir is a Hebrew surname most famously borne by Golda Meir, the former Prime Minister of Israel.
-
C.
Chaim
Chaim is a given name notably borne by Chaim Weizmann, the first President of the State of Israel and a prominent Zionist leader and chemist.
-
D.
Hanoch
Hanoch is a biblical figure listed in the Hebrew Bible as one of the descendants of Abraham through Keturah and Midian.
-
E.
Jeremy Ashkenas
Jeremy Ashkenas is an American programmer and open-source developer best known for creating the CoffeeScript language and contributing to projects like Backbone.js and Underscore.js.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada269a9188190aada5b3799d4dfd7 |
completed | March 8, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2037cc5fc819084a441ebb045142b |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:03 p.m.