Triple
T10470587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dante's Peak |
E246911
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Howard Smith
Howard Smith is a film editor best known for his work on major Hollywood productions, including the disaster film "Dante's Peak."
|
E868173
|
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: Howard Smith | Statement: [Dante's Peak, editedBy, Howard Smith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Smith Context triple: [Dante's Peak, editedBy, Howard Smith]
-
A.
Howard Smith
Howard Smith was an American character actor known for his supporting roles in mid-20th-century films and television, often portraying gruff authority figures.
-
B.
Chris Haywood
Chris Haywood is an Australian actor known for his extensive work in film, television, and theatre since the 1970s.
-
C.
Chris Smith
Chris Smith is a long-serving Republican U.S. Representative from New Jersey known for his work on human rights and veterans’ issues.
-
D.
Richard Smith
Richard Smith is a son of Frederick W. Smith, the American businessman best known as the founder of FedEx.
-
E.
Howard Dwight Smith
Howard Dwight Smith was an American architect best known for designing Ohio Stadium at Ohio State University.
- 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: Howard Smith Triple: [Dante's Peak, editedBy, Howard Smith]
Generated description
Howard Smith is a film editor best known for his work on major Hollywood productions, including the disaster film "Dante's Peak."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Howard Smith Target entity description: Howard Smith is a film editor best known for his work on major Hollywood productions, including the disaster film "Dante's Peak."
-
A.
Howard Smith
Howard Smith was an American character actor known for his supporting roles in mid-20th-century films and television, often portraying gruff authority figures.
-
B.
Chris Haywood
Chris Haywood is an Australian actor known for his extensive work in film, television, and theatre since the 1970s.
-
C.
Chris Smith
Chris Smith is a long-serving Republican U.S. Representative from New Jersey known for his work on human rights and veterans’ issues.
-
D.
Richard Smith
Richard Smith is a son of Frederick W. Smith, the American businessman best known as the founder of FedEx.
-
E.
Howard Dwight Smith
Howard Dwight Smith was an American architect best known for designing Ohio Stadium at Ohio State University.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509305fec81908b1acd91ae1f875d |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90db8b1288190bb6bb064cb0724e0 |
completed | April 10, 2026, 2:48 p.m. |
| NEDg | Description generation | batch_69d9100604e08190b744b361d60188d5 |
completed | April 10, 2026, 2:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d910a1cdb88190988db41e97341ed9 |
completed | April 10, 2026, 3 p.m. |
Created at: April 6, 2026, 12:20 p.m.