Triple
T11937838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gary Gilmore |
E284092
|
entity |
| Predicate | victimOfCrime |
P870
|
FINISHED |
| Object |
Max Jensen
Max Jensen was a young gas station attendant in Utah who became one of the two murder victims of convicted killer Gary Gilmore in 1976.
|
E955013
|
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: Max Jensen | Statement: [Gary Gilmore, victimOfCrime, Max Jensen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Max Jensen Context triple: [Gary Gilmore, victimOfCrime, Max Jensen]
-
A.
Jon Jensen
Jon Jensen is the central protagonist of the film "The Salvation," around whom the story’s dramatic events and conflicts revolve.
-
B.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
C.
Johnny Jorgensen
Johnny Jorgensen was a professional basketball player best known for his time in the early Basketball Association of America, including a stint with the Cleveland Rebels.
-
D.
Erik Jendresen
Erik Jendresen is an American writer and producer best known for his work on the acclaimed World War II miniseries "Band of Brothers."
-
E.
Kurt Jensen
Kurt Jensen was a microbiologist known for co-developing the Lowenstein–Jensen medium, a key culture medium used in the diagnosis of tuberculosis.
- 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: Max Jensen Triple: [Gary Gilmore, victimOfCrime, Max Jensen]
Generated description
Max Jensen was a young gas station attendant in Utah who became one of the two murder victims of convicted killer Gary Gilmore in 1976.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Max Jensen Target entity description: Max Jensen was a young gas station attendant in Utah who became one of the two murder victims of convicted killer Gary Gilmore in 1976.
-
A.
Jon Jensen
Jon Jensen is the central protagonist of the film "The Salvation," around whom the story’s dramatic events and conflicts revolve.
-
B.
Matthew Jensen
Matthew Jensen is a cinematographer best known for his work on major films such as the 2017 superhero movie "Wonder Woman."
-
C.
Johnny Jorgensen
Johnny Jorgensen was a professional basketball player best known for his time in the early Basketball Association of America, including a stint with the Cleveland Rebels.
-
D.
Erik Jendresen
Erik Jendresen is an American writer and producer best known for his work on the acclaimed World War II miniseries "Band of Brothers."
-
E.
Kurt Jensen
Kurt Jensen was a microbiologist known for co-developing the Lowenstein–Jensen medium, a key culture medium used in the diagnosis of tuberculosis.
- 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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903094218819092e11b273d87de65 |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4408d497c8190b051225140125e1f |
completed | May 1, 2026, 5:56 a.m. |
| NEDg | Description generation | batch_69f448fc874081908fe05f9d8aff11a3 |
completed | May 1, 2026, 6:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f44afdc7b08190bdf47cfcb94c34c8 |
completed | May 1, 2026, 6:41 a.m. |
Created at: April 8, 2026, 9:45 p.m.