Triple
T1723364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jonathan Sacks |
E37441
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sacks
Sacks is a surname most prominently associated with Jonathan Sacks, the influential British rabbi, philosopher, and former Chief Rabbi of the United Hebrew Congregations of the Commonwealth.
|
E195124
|
NE FINISHED |
How this triple was built (4 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: Sacks | Statement: [Jonathan Sacks, familyName, Sacks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sacks Context triple: [Jonathan Sacks, familyName, Sacks]
-
A.
Logue
Logue is a surname most notably associated with Lionel Logue, the Australian speech therapist who helped King George VI overcome his stammer.
-
B.
Saunders
Saunders is a given name most notably borne by Saunders Mac Lane, a prominent American mathematician and co-founder of category theory.
-
C.
Mr. Papers
Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
-
D.
The Saint
The Saint is one of the short stories in Gabriel García Márquez’s collection "Strange Pilgrims," exploring themes of faith, miracles, and human vulnerability.
-
E.
Millner
Millner is an English occupational surname historically associated with people who made or sold hats or millinery goods.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sacks Triple: [Jonathan Sacks, familyName, Sacks]
Generated description
Sacks is a surname most prominently associated with Jonathan Sacks, the influential British rabbi, philosopher, and former Chief Rabbi of the United Hebrew Congregations of the Commonwealth.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sacks Target entity description: Sacks is a surname most prominently associated with Jonathan Sacks, the influential British rabbi, philosopher, and former Chief Rabbi of the United Hebrew Congregations of the Commonwealth.
-
A.
Logue
Logue is a surname most notably associated with Lionel Logue, the Australian speech therapist who helped King George VI overcome his stammer.
-
B.
Saunders
Saunders is a given name most notably borne by Saunders Mac Lane, a prominent American mathematician and co-founder of category theory.
-
C.
Mr. Papers
Mr. Papers is a rapper best known for his on-and-off romantic relationship with hip-hop icon Lil' Kim.
-
D.
The Saint
The Saint is one of the short stories in Gabriel García Márquez’s collection "Strange Pilgrims," exploring themes of faith, miracles, and human vulnerability.
-
E.
Resnick
Resnick is a surname most notably associated with Mitchel Resnick, an influential researcher in learning sciences and creative technologies at the MIT Media Lab.
- F. None of above. chosen
Provenance (5 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa63587ce08190a6a9e6dae11a708c |
completed | March 6, 2026, 5:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8aefefc881908acd48eebc67c6ec |
completed | March 8, 2026, 2:42 p.m. |
| NEDg | Description generation | batch_69ad979ce880819089daecbc8455ec84 |
completed | March 8, 2026, 3:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad9ba92a848190918a8748fb65348a |
completed | March 8, 2026, 3:54 p.m. |
Created at: March 4, 2026, 7:30 p.m.