Triple
T11049821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come to Daddy |
E261215
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object |
Daniel Katz
Daniel Katz is a cinematographer known for his work on the darkly comedic horror film "Come to Daddy."
|
E952123
|
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: Daniel Katz | Statement: [Come to Daddy, cinematographyBy, Daniel Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Katz Context triple: [Come to Daddy, cinematographyBy, Daniel Katz]
-
A.
Daniel Katz
Daniel Katz is an environmental activist and social entrepreneur best known for co-founding the Rainforest Alliance, a leading international conservation and sustainability organization.
-
B.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
C.
Lewis Katz
Lewis Katz was an American businessman, philanthropist, and co-owner of the Philadelphia Inquirer known for his major charitable contributions to education and medicine.
-
D.
Jason Katz
Jason Katz is an American screenwriter and story artist best known for his work on Pixar animated films.
-
E.
Stephen Katz
Stephen Katz is a humorous, bumbling yet loyal companion character in Bill Bryson’s travel memoir "A Walk in the Woods," known for his comic misadventures on the Appalachian Trail.
- 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: Daniel Katz Triple: [Come to Daddy, cinematographyBy, Daniel Katz]
Generated description
Daniel Katz is a cinematographer known for his work on the darkly comedic horror film "Come to Daddy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Daniel Katz Target entity description: Daniel Katz is a cinematographer known for his work on the darkly comedic horror film "Come to Daddy."
-
A.
Daniel Katz
Daniel Katz is an environmental activist and social entrepreneur best known for co-founding the Rainforest Alliance, a leading international conservation and sustainability organization.
-
B.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
C.
Lewis Katz
Lewis Katz was an American businessman, philanthropist, and co-owner of the Philadelphia Inquirer known for his major charitable contributions to education and medicine.
-
D.
Jason Katz
Jason Katz is an American screenwriter and story artist best known for his work on Pixar animated films.
-
E.
Stephen Katz
Stephen Katz is a humorous, bumbling yet loyal companion character in Bill Bryson’s travel memoir "A Walk in the Woods," known for his comic misadventures on the Appalachian Trail.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79868c78881908c8e3672c05ae7ec |
completed | April 9, 2026, 12:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f28053fe08819099e848cd74b989a0 |
completed | April 29, 2026, 10:04 p.m. |
| NEDg | Description generation | batch_69f40b2d0a388190a11a0e2d806e310b |
completed | May 1, 2026, 2:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f40deb4eec8190a8fe1aa59b1514e6 |
completed | May 1, 2026, 2:20 a.m. |
Created at: April 8, 2026, 9:26 p.m.