Triple
T2834742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sarafina! |
E62321
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
David Heitner
David Heitner is a film editor known for his work on the South African musical drama film "Sarafina!".
|
E302639
|
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 Heitner | Statement: [Sarafina!, editedBy, David Heitner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Heitner Context triple: [Sarafina!, editedBy, David Heitner]
-
A.
Michael Kaplan
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
-
B.
Jeremy Shamos
Jeremy Shamos is an American stage and screen actor known for his work on Broadway and in film and television.
-
C.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
-
D.
Jon Oberheide
Jon Oberheide is a cybersecurity entrepreneur and researcher best known as the co-founder and former CTO of Duo Security, a leading multi-factor authentication and zero-trust security company.
-
E.
Matthew C. Brown
Matthew C. Brown is a film producer known for his work on the horror movie "Spectral."
- 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 Heitner Triple: [Sarafina!, editedBy, David Heitner]
Generated description
David Heitner is a film editor known for his work on the South African musical drama film "Sarafina!".
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: David Heitner Target entity description: David Heitner is a film editor known for his work on the South African musical drama film "Sarafina!".
-
A.
Michael Kaplan
Michael Kaplan is a composer and musician known for creating the music for the film "Burlesque."
-
B.
Jeremy Shamos
Jeremy Shamos is an American stage and screen actor known for his work on Broadway and in film and television.
-
C.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
-
D.
Jon Oberheide
Jon Oberheide is a cybersecurity entrepreneur and researcher best known as the co-founder and former CTO of Duo Security, a leading multi-factor authentication and zero-trust security company.
-
E.
Matthew C. Brown
Matthew C. Brown is a film producer known for his work on the horror movie "Spectral."
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdec18b808190aedae2ed11d53b15 |
completed | March 7, 2026, 8:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8c45c548190ac67b94a845cc730 |
completed | March 10, 2026, 9:47 a.m. |
| NEDg | Description generation | batch_69afe9a000c4819085be1794bff0d506 |
completed | March 10, 2026, 9:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0010b0ddc8190b4bfb18448f88077 |
completed | March 10, 2026, 11:31 a.m. |
Created at: March 6, 2026, 10:01 p.m.