Triple
T12745414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talmud Yerushalmi |
E304590
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Nezikin |
E553441
|
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: Nezikin | Statement: [Talmud Yerushalmi, hasPart, Nezikin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nezikin Context triple: [Talmud Yerushalmi, hasPart, Nezikin]
-
A.
Nezikin
chosen
Nezikin is the order of the Mishnah that deals primarily with civil and criminal law, including damages, property, and judicial procedures in Jewish law.
-
B.
Zgonik
Zgonik is the Slovene name for Sgonico, a small municipality in the Friuli Venezia Giulia region of northeastern Italy near the border with Slovenia.
-
C.
Zezuru
Zezuru is a major dialect of the Shona language spoken primarily in central and northern Zimbabwe.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Zueitina
Zueitina is a Libyan coastal town known primarily for its strategic oil terminal and role in the country’s petroleum export infrastructure.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96bd42fe08190a85467b1a998d2af |
completed | April 10, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c94265481908ace9cac757df890 |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 9, 2026, 5:26 p.m.