Triple
T16526931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | X-Press 2 |
E401463
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object |
Smoke Machine
"Smoke Machine" is a house music track by British electronic duo X-Press 2, known for its club-oriented production and role in their early 2000s success.
|
E1218067
|
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: Smoke Machine | Statement: [X-Press 2, notableSong, Smoke Machine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Smoke Machine Context triple: [X-Press 2, notableSong, Smoke Machine]
-
A.
The Smoke
The Smoke is the English name of Surah Ad-Dukhan, a chapter of the Qur’an that warns of a coming smoke as a sign of divine punishment and emphasizes God’s power and mercy.
-
B.
The Smoke
The Smoke is a dramatic work by British playwright Lucy Kirkwood, known for her sharp, socially engaged storytelling.
-
C.
The Smoke
The Smoke is a British television drama series centered on the lives and challenges of London firefighters.
-
D.
“Smoke”
“Smoke” is a short story by Ivan Turgenev that explores themes of love, disillusionment, and the clash between old and new Russian society.
-
E.
“Smoke”
“Smoke” is a short story by William Faulkner featuring the shrewd small-town lawyer Gavin Stevens as he unravels a mysterious crime.
- 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: Smoke Machine Triple: [X-Press 2, notableSong, Smoke Machine]
Generated description
"Smoke Machine" is a house music track by British electronic duo X-Press 2, known for its club-oriented production and role in their early 2000s success.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Smoke Machine Target entity description: "Smoke Machine" is a house music track by British electronic duo X-Press 2, known for its club-oriented production and role in their early 2000s success.
-
A.
The Smoke
The Smoke is a dramatic work by British playwright Lucy Kirkwood, known for her sharp, socially engaged storytelling.
-
B.
The Smoke
The Smoke is the English name of Surah Ad-Dukhan, a chapter of the Qur’an that warns of a coming smoke as a sign of divine punishment and emphasizes God’s power and mercy.
-
C.
The Smoke
The Smoke is a British television drama series centered on the lives and challenges of London firefighters.
-
D.
“Smoke”
“Smoke” is a short story by William Faulkner featuring the shrewd small-town lawyer Gavin Stevens as he unravels a mysterious crime.
-
E.
“Smoke”
“Smoke” is a short story by Ivan Turgenev that explores themes of love, disillusionment, and the clash between old and new Russian society.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed4b8a08190b5f179fc583001a6 |
completed | April 18, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00608d36dc8190a094fa4513147c85 |
completed | May 10, 2026, 10:40 a.m. |
| NEDg | Description generation | batch_6a0061a6e1e88190a5efe0430db0bd9b |
completed | May 10, 2026, 10:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00627908988190803707069872e4c5 |
completed | May 10, 2026, 10:48 a.m. |
Created at: April 10, 2026, 5:14 a.m.