Triple
T12304845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reichman University |
E293326
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Uriel Reichman |
E975672
|
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: Uriel Reichman | Statement: [Reichman University, founder, Uriel Reichman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uriel Reichman Context triple: [Reichman University, founder, Uriel Reichman]
-
A.
Uriel Reichman
chosen
Uriel Reichman is an Israeli legal scholar and academic leader best known as the founder and first president of Reichman University (formerly IDC Herzliya).
-
B.
Yoel Herzog
Yoel Herzog is a member of the prominent Herzog family, known primarily as a son of former Israeli president Chaim Herzog.
-
C.
Uriel Frisch
Uriel Frisch is a French physicist and mathematician renowned for his contributions to fluid dynamics and turbulence theory.
-
D.
Uriel Feige
Uriel Feige is an Israeli computer scientist known for his influential work in computational complexity theory, approximation algorithms, and probabilistically checkable proofs.
-
E.
Yaacov Agam
Yaacov Agam is an Israeli sculptor and experimental artist renowned as a pioneer of kinetic and optical art.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93edca2648190987eef19599e340c |
completed | April 10, 2026, 6:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a9b8ef88190bce122f1b1800cd4 |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:53 p.m.