Triple
T8333386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Sacks |
E195124
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jonathan |
E44008
|
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: Jonathan | Statement: [Jonathan Sacks, givenName, Jonathan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Context triple: [Jonathan Sacks, givenName, Jonathan]
-
A.
Jonathan
chosen
Jonathan is a common masculine given name of Hebrew origin, meaning "Yahweh has given."
-
B.
Jeffrey
Jeffrey is a masculine given name of Germanic origin, commonly used in English-speaking countries.
-
C.
Jeremy
"Jeremy" is a widely acclaimed Pearl Jam song, known for its haunting narrative about a troubled youth and its powerful, socially charged music video.
-
D.
Jeremy
Jeremy is the given name of American actor Jeremy Ray Taylor, known for his role as Ben Hanscom in the horror film "It" (2017).
-
E.
Jeremy
Jeremy is one of the central male protagonists in the romantic comedy film "Think Like a Man," which follows a group of men whose relationships are upended when their partners start using advice from Steve Harvey’s dating book.
- 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fbe61f481909cde8ab2c42f89fc |
completed | March 31, 2026, 8:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc71005f0819092c46fa5a43f2a15 |
completed | April 2, 2026, 1:32 a.m. |
Created at: March 30, 2026, 5:57 p.m.