Triple
T17416984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hebrew revival movement |
E423514
|
entity |
| Predicate | hasKeyFigure |
P810
|
FINISHED |
| Object |
David Yellin
David Yellin was a prominent Jewish educator and linguist who played a central role in shaping and standardizing modern Hebrew.
|
E1335519
|
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: David Yellin | Statement: [Hebrew revival movement, hasKeyFigure, David Yellin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Yellin Context triple: [Hebrew revival movement, hasKeyFigure, David Yellin]
-
A.
Ben Dorfman
Ben Dorfman is a fictional character in Woody Allen’s 2016 romantic comedy film "Café Society."
-
B.
Bennett Yellin
Bennett Yellin is an American screenwriter best known for co-writing the hit comedy film "Dumb and Dumber."
-
C.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
D.
Steven Fierberg
Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
-
E.
Michael Nudelman
Michael Nudelman was an Israeli politician and Knesset member known for representing Russian-speaking immigrants and serving in several immigrant-focused political parties.
- 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: David Yellin Triple: [Hebrew revival movement, hasKeyFigure, David Yellin]
Generated description
David Yellin was a prominent Jewish educator and linguist who played a central role in shaping and standardizing modern Hebrew.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Yellin Target entity description: David Yellin was a prominent Jewish educator and linguist who played a central role in shaping and standardizing modern Hebrew.
-
A.
Ben Dorfman
Ben Dorfman is a fictional character in Woody Allen’s 2016 romantic comedy film "Café Society."
-
B.
Bennett Yellin
Bennett Yellin is an American screenwriter best known for co-writing the hit comedy film "Dumb and Dumber."
-
C.
Daniel Ullman
Daniel Ullman was an American screenwriter known for his work on mid-20th-century genre films, particularly Westerns and thrillers.
-
D.
Steven Fierberg
Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
-
E.
Michael Nudelman
Michael Nudelman was an Israeli politician and Knesset member known for representing Russian-speaking immigrants and serving in several immigrant-focused political parties.
- 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_69d889d7d27c819088486ce3f0627fa1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e44232ecdc8190ac8958c1780fea19 |
completed | April 19, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a051701512c819080be8649f1f1b401 |
completed | May 14, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_6a05184e0cc881909aad820f5afc34be |
completed | May 14, 2026, 12:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a05189feab08190ad33ec2f5711fecb |
completed | May 14, 2026, 12:34 a.m. |
Created at: April 10, 2026, 5:46 a.m.