Triple
T15122109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purpose |
E361194
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Axident
Axident is a Norwegian record producer and songwriter known for crafting pop and electronic hits for international artists.
|
E1137762
|
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: Axident | Statement: [Purpose, producer, Axident]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Axident Context triple: [Purpose, producer, Axident]
-
A.
The Accident
The Accident is a semi-autobiographical novel by Elie Wiesel that explores trauma, survival, and identity in the aftermath of the Holocaust.
-
B.
The Accident
The Accident is a British television drama series in which Abigail Cruttenden appears, centered on the aftermath of a devastating industrial disaster in a small Welsh town.
-
C.
Crashout
Crashout is a 1955 American film noir crime drama about a group of escaped convicts on a violent quest for hidden loot.
-
D.
The Crash
The Crash is a 1928 American drama film, best known as a silent-era production featuring actor William Janney.
-
E.
The Next Accident
The Next Accident is a suspenseful crime thriller novel by bestselling American author Lisa Gardner, featuring FBI profiler Pierce Quincy investigating a series of deadly, seemingly accidental events.
- 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: Axident Triple: [Purpose, producer, Axident]
Generated description
Axident is a Norwegian record producer and songwriter known for crafting pop and electronic hits for international artists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Axident Target entity description: Axident is a Norwegian record producer and songwriter known for crafting pop and electronic hits for international artists.
-
A.
The Accident
The Accident is a semi-autobiographical novel by Elie Wiesel that explores trauma, survival, and identity in the aftermath of the Holocaust.
-
B.
The Accident
The Accident is a British television drama series in which Abigail Cruttenden appears, centered on the aftermath of a devastating industrial disaster in a small Welsh town.
-
C.
Crashout
Crashout is a 1955 American film noir crime drama about a group of escaped convicts on a violent quest for hidden loot.
-
D.
The Crash
The Crash is a 1928 American drama film, best known as a silent-era production featuring actor William Janney.
-
E.
The Next Accident
The Next Accident is a suspenseful crime thriller novel by bestselling American author Lisa Gardner, featuring FBI profiler Pierce Quincy investigating a series of deadly, seemingly accidental events.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0059f69a881909929a037a0eef702 |
completed | April 15, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7f4abd08190b47c9daff2921919 |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69feb8bb774481908272929358817440 |
completed | May 9, 2026, 4:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feb9384b4c81909fe80dec3abc1659 |
completed | May 9, 2026, 4:34 a.m. |
Created at: April 10, 2026, 3:06 a.m.