Triple
T3321602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oh! What a Lovely War |
E69806
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Kevin Connor
Kevin Connor is a film editor known for his work on the satirical World War I musical film "Oh! What a Lovely War."
|
E373591
|
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: Kevin Connor | Statement: [Oh! What a Lovely War, editedBy, Kevin Connor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kevin Connor Context triple: [Oh! What a Lovely War, editedBy, Kevin Connor]
-
A.
Marc Connelly
Marc Connelly was an American playwright, director, and member of the Algonquin Round Table who won the Pulitzer Prize for Drama for "The Green Pastures."
-
B.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
C.
Kevin Corrigan
Kevin Corrigan is an American character actor known for his offbeat, often darkly comic supporting roles in numerous independent films and major studio movies.
-
D.
Martin Connor
Martin Connor is a film editor known for his work on the biographical war drama "The Railway Man."
-
E.
Kevin Cossom
Kevin Cossom is an American singer, songwriter, and record producer known for his R&B and hip-hop collaborations and songwriting for major artists.
- 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: Kevin Connor Triple: [Oh! What a Lovely War, editedBy, Kevin Connor]
Generated description
Kevin Connor is a film editor known for his work on the satirical World War I musical film "Oh! What a Lovely War."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kevin Connor Target entity description: Kevin Connor is a film editor known for his work on the satirical World War I musical film "Oh! What a Lovely War."
-
A.
Marc Connelly
Marc Connelly was an American playwright, director, and member of the Algonquin Round Table who won the Pulitzer Prize for Drama for "The Green Pastures."
-
B.
Kevin O'Connell
Kevin O'Connell is an American football coach and former NFL quarterback who serves as the head coach of the Minnesota Vikings.
-
C.
Kevin Corrigan
Kevin Corrigan is an American character actor known for his offbeat, often darkly comic supporting roles in numerous independent films and major studio movies.
-
D.
Martin Connor
Martin Connor is a film editor known for his work on the biographical war drama "The Railway Man."
-
E.
Kevin Cossom
Kevin Cossom is an American singer, songwriter, and record producer known for his R&B and hip-hop collaborations and songwriting for major artists.
- 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb13b85208190b13aba355d5dafcf |
completed | March 8, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b432ee11988190843e4b81500b65ca |
completed | March 13, 2026, 3:53 p.m. |
| NEDg | Description generation | batch_69b435bbe10c81908b767265371c1b53 |
completed | March 13, 2026, 4:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4396462548190ab0a17931c198bd7 |
completed | March 13, 2026, 4:20 p.m. |
Created at: March 8, 2026, 3:11 p.m.