Triple
T12712907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hashomer |
E303765
|
entity |
| Predicate | member |
P10
|
FINISHED |
| Object | Manya Shochat |
E904924
|
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: Manya Shochat | Statement: [Hashomer, member, Manya Shochat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manya Shochat Context triple: [Hashomer, member, Manya Shochat]
-
A.
Manya Shochat
chosen
Manya Shochat was a pioneering Zionist activist and organizer, often called the "mother of the kibbutz," who played a key role in establishing early Jewish agricultural collectives in Ottoman Palestine.
-
B.
Daphna Kastner
Daphna Kastner is a Canadian actress, screenwriter, and director known for her work in independent films.
-
C.
Orit Gadiesh
Orit Gadiesh is an Israeli-American businesswoman and longtime chair of the global management consulting firm Bain & Company, known for her influence in corporate strategy and leadership.
-
D.
Yona Wallach
Yona Wallach was an influential Israeli poet known for her experimental, provocative, and psychologically charged Hebrew poetry that challenged social and sexual norms.
-
E.
Sharon Shoham
Sharon Shoham is a computer scientist known for her research in formal methods and verification, and for being a doctoral student of Orna Kupferman.
- 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_69d7bdf084148190ab9d513dc0735af4 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96208fa6481909d6fd43654752a2d |
completed | April 10, 2026, 8:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b8a79488190aaf95d4f2e20a7bc |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:23 p.m.