Triple
T1013296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oded Goldreich |
E21871
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Rehovot |
E110760
|
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: Rehovot | Statement: [Oded Goldreich, workLocation, Rehovot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rehovot Context triple: [Oded Goldreich, workLocation, Rehovot]
-
A.
Rehovot
chosen
Rehovot is a city in central Israel known for its scientific and agricultural research institutions, including the Weizmann Institute of Science.
-
B.
Herzliya
Herzliya is a coastal city in central Israel known as a high-tech and academic hub, home to major technology companies and institutions.
-
C.
Kiryat Ono
Kiryat Ono is a small suburban city in central Israel, located in the Tel Aviv metropolitan area.
-
D.
Givatayim
Givatayim is a small, densely populated city in Israel’s Tel Aviv metropolitan area, known for its residential character and proximity to major urban centers.
-
E.
Kiryat Shmona
Kiryat Shmona is a northern Israeli city near the Lebanese border, known for its strategic location and frequent exposure to cross-border conflict.
- 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_69a493c68e24819080ed0ee8bcfd5ce0 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b7a8b254819089ffed9cb62a6930 |
completed | March 1, 2026, 10:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad230d2870819099001561e36078f5 |
completed | March 8, 2026, 7:19 a.m. |
Created at: March 1, 2026, 7:41 p.m.