Triple
T19881767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sefer HaHezyonot |
E477790
|
entity |
| Predicate | relatedWorkByAuthor |
P922
|
FINISHED |
| Object | Etz Hayyim |
—
|
NE NERFINISHED |
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: Etz Hayyim | Statement: [Sefer HaHezyonot, relatedWorkByAuthor, Etz Hayyim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Etz Hayyim Context triple: [Sefer HaHezyonot, relatedWorkByAuthor, Etz Hayyim]
-
A.
Etz Chaim
chosen
Etz Chaim is a foundational Kabbalistic work, primarily associated with Rabbi Isaac Luria’s mystical teachings as compiled by his disciple Rabbi Chaim Vital.
-
B.
Jerusalem Forest
Jerusalem Forest is a large woodland area on the western outskirts of Jerusalem, known for its hiking trails, scenic viewpoints, and natural respite from the urban environment.
-
C.
הר הזיתים
הר הזיתים הוא הר מרכזי במזרח ירושלים בעל חשיבות דתית והיסטורית רבה ליהדות, לנצרות ולאסלאם, ובו אחד מבתי הקברות היהודיים העתיקים והגדולים בעולם.
-
D.
רמת גן
רמת גן היא עיר במרכז ישראל, הסמוכה לתל אביב, הידועה בריכוז מוסדות הבריאות, הפארקים והמרכזים העסקיים שבה.
-
E.
Hy Zaret
Hy Zaret was an American songwriter best known for penning the lyrics to the classic ballad "Unchained Melody."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658df3f5c81909b5b290de91b8d50 |
completed | April 20, 2026, 4:48 p.m. |
Created at: April 10, 2026, 1:52 p.m.