Triple
T8840142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fallin’ Up: My Story |
E210364
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object |
Steve Dennis
Steve Dennis is a writer best known for co-authoring the memoir "Fallin’ Up: My Story."
|
E767393
|
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: Steve Dennis | Statement: [Fallin’ Up: My Story, author, Steve Dennis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Dennis Context triple: [Fallin’ Up: My Story, author, Steve Dennis]
-
A.
Steve David
Steve David was a prolific Trinidadian forward best known for his goal-scoring exploits in the North American Soccer League during the 1970s.
-
B.
Jeff Danna
Jeff Danna is a Canadian film composer known for his scores for movies such as The Boondock Saints and various animated and dramatic films.
-
C.
Dennis Alan
Dennis Alan is the main protagonist of the horror film "The Serpent and the Rainbow," a Harvard anthropologist who investigates Haitian voodoo and zombification.
-
D.
Steve Judd
Steve Judd is the aging, principled former lawman at the heart of the Western film "Ride the High Country," whose moral integrity drives the story’s central conflict.
-
E.
David Denman
David Denman is an American actor best known for his role as Roy Anderson on the U.S. version of "The Office" and for supporting performances in films and television series across comedy and drama.
- 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: Steve Dennis Triple: [Fallin’ Up: My Story, author, Steve Dennis]
Generated description
Steve Dennis is a writer best known for co-authoring the memoir "Fallin’ Up: My Story."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steve Dennis Target entity description: Steve Dennis is a writer best known for co-authoring the memoir "Fallin’ Up: My Story."
-
A.
Steve David
Steve David was a prolific Trinidadian forward best known for his goal-scoring exploits in the North American Soccer League during the 1970s.
-
B.
Jeff Danna
Jeff Danna is a Canadian film composer known for his scores for movies such as The Boondock Saints and various animated and dramatic films.
-
C.
Dennis Alan
Dennis Alan is the main protagonist of the horror film "The Serpent and the Rainbow," a Harvard anthropologist who investigates Haitian voodoo and zombification.
-
D.
Steve Judd
Steve Judd is the aging, principled former lawman at the heart of the Western film "Ride the High Country," whose moral integrity drives the story’s central conflict.
-
E.
David Denman
David Denman is an American actor best known for his role as Roy Anderson on the U.S. version of "The Office" and for supporting performances in films and television series across comedy and drama.
- 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_69ca8388549c819095fd94eadefbb007 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6085fe24819095139f18da92d7e7 |
completed | April 1, 2026, 12:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1c1488c8190ac7b6a13d3af8be6 |
completed | April 3, 2026, 1:33 p.m. |
| NEDg | Description generation | batch_69cfc363c3b88190ae61d54ea45e4016 |
completed | April 3, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfc3b44ba481909e43beebde33930b |
completed | April 3, 2026, 1:42 p.m. |
Created at: March 30, 2026, 6:48 p.m.