Triple
T2230465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamilton |
E48751
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Sander Jacobs
Sander Jacobs is a film and television producer known for his work on the acclaimed musical film adaptation of "Hamilton."
|
E257061
|
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: Sander Jacobs | Statement: [Hamilton, producer, Sander Jacobs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sander Jacobs Context triple: [Hamilton, producer, Sander Jacobs]
-
A.
Sander Loones
Sander Loones is a Belgian politician and member of the New Flemish Alliance (N-VA) who has served in both national and European political roles.
-
B.
Sjoerd Soeters
Sjoerd Soeters is a Dutch architect known for his postmodern, human-scaled urban designs and influential waterfront redevelopment projects in the Netherlands.
-
C.
Sander Dieleman
Sander Dieleman is a machine learning researcher known for his influential work in deep learning for audio and music, including contributions to models such as WaveNet.
-
D.
Tim Kruithoff
Tim Kruithoff is a German local politician who serves as the mayor of the city of Emden in Lower Saxony.
-
E.
Christian Huitema
Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
- 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: Sander Jacobs Triple: [Hamilton, producer, Sander Jacobs]
Generated description
Sander Jacobs is a film and television producer known for his work on the acclaimed musical film adaptation of "Hamilton."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sander Jacobs Target entity description: Sander Jacobs is a film and television producer known for his work on the acclaimed musical film adaptation of "Hamilton."
-
A.
Sander Loones
Sander Loones is a Belgian politician and member of the New Flemish Alliance (N-VA) who has served in both national and European political roles.
-
B.
Sjoerd Soeters
Sjoerd Soeters is a Dutch architect known for his postmodern, human-scaled urban designs and influential waterfront redevelopment projects in the Netherlands.
-
C.
Sander Dieleman
Sander Dieleman is a machine learning researcher known for his influential work in deep learning for audio and music, including contributions to models such as WaveNet.
-
D.
Tim Kruithoff
Tim Kruithoff is a German local politician who serves as the mayor of the city of Emden in Lower Saxony.
-
E.
Christian Huitema
Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc069e0ac8190bcda8cba9f5c7a5d |
completed | March 7, 2026, 6:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae95fb20b88190b7e959b5d718fe73 |
completed | March 9, 2026, 9:42 a.m. |
| NEDg | Description generation | batch_69ae96c5a6308190b970ec78984a4e8a |
completed | March 9, 2026, 9:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae9728ebc081908e00e318bcd60e57 |
completed | March 9, 2026, 9:47 a.m. |
Created at: March 4, 2026, 7:47 p.m.