Triple
T2732387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elf |
E60344
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
David Berenbaum
David Berenbaum is an American screenwriter best known for writing the popular Christmas comedy film "Elf."
|
E292624
|
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 Berenbaum | Statement: [Elf, screenwriter, David Berenbaum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Berenbaum Context triple: [Elf, screenwriter, David Berenbaum]
-
A.
Michael Berenbaum
Michael Berenbaum is an American film and television editor known for his work on numerous popular comedies and dramas.
-
B.
Jonathan Bornstein
Jonathan Bornstein is an American soccer player and defender best known for his long career in Major League Soccer and appearances with the United States men's national team.
-
C.
Edwin Schlossberg
Edwin Schlossberg is an American designer, artist, and author known for his innovative work in interactive museum and exhibition design.
-
D.
Paul Feldman
Paul Feldman is a computer scientist and cryptographer known for his work on digital signatures and other foundational topics in modern cryptography.
-
E.
Shlomo Ganzfried
Shlomo Ganzfried was a 19th-century Hungarian rabbi and halachic authority best known for composing the widely used concise code of Jewish law, the Kitzur Shulchan Aruch.
- 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 Berenbaum Triple: [Elf, screenwriter, David Berenbaum]
Generated description
David Berenbaum is an American screenwriter best known for writing the popular Christmas comedy film "Elf."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Berenbaum Target entity description: David Berenbaum is an American screenwriter best known for writing the popular Christmas comedy film "Elf."
-
A.
Michael Berenbaum
Michael Berenbaum is an American film and television editor known for his work on numerous popular comedies and dramas.
-
B.
Jonathan Bornstein
Jonathan Bornstein is an American soccer player and defender best known for his long career in Major League Soccer and appearances with the United States men's national team.
-
C.
Edwin Schlossberg
Edwin Schlossberg is an American designer, artist, and author known for his innovative work in interactive museum and exhibition design.
-
D.
Paul Feldman
Paul Feldman is a computer scientist and cryptographer known for his work on digital signatures and other foundational topics in modern cryptography.
-
E.
Shlomo Ganzfried
Shlomo Ganzfried was a 19th-century Hungarian rabbi and halachic authority best known for composing the widely used concise code of Jewish law, the Kitzur Shulchan Aruch.
- 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_69ab4b75cd908190b691ef0d1801acda |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdaf011548190beb9c3feee7b743f |
completed | March 7, 2026, 7:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afb69eeedc81908ad654de9e1259ea |
completed | March 10, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69afb703a5f8819097b71e19db11feaf |
completed | March 10, 2026, 6:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afb7acf3588190813bde4428dfe5f4 |
completed | March 10, 2026, 6:18 a.m. |
Created at: March 6, 2026, 9:56 p.m.