Triple
T13600929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kala |
E324937
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
The Turn
"The Turn" is a song by the artist Kala.
|
E1051035
|
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: The Turn | Statement: [Kala, hasTrack, The Turn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Turn Context triple: [Kala, hasTrack, The Turn]
-
A.
The Turn
The Turn is a track from M.I.A.'s debut album "Arular," showcasing her distinctive blend of electronic, hip hop, and global dance influences.
-
B.
The Turning Point
The Turning Point is a 1977 American drama film about the world of professional ballet, noted for its performances by Shirley MacLaine, Anne Bancroft, and Mikhail Baryshnikov.
-
C.
The Turning Point
The Turning Point is a notable work by James Mitchell, likely recognized as one of his significant literary or creative contributions.
-
D.
The Mustering
The Mustering is the English-titled installment of the fantasy series "The Exile," likely depicting a pivotal gathering or preparation for conflict within its narrative world.
-
E.
The Turning
The Turning is a 2020 supernatural horror film loosely based on Henry James's novella "The Turn of the Screw," following a governess who encounters disturbing forces while caring for two orphaned children in a mysterious estate.
- 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: The Turn Triple: [Kala, hasTrack, The Turn]
Generated description
"The Turn" is a song by the artist Kala.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Turn Target entity description: "The Turn" is a song by the artist Kala.
-
A.
The Turn
The Turn is a track from M.I.A.'s debut album "Arular," showcasing her distinctive blend of electronic, hip hop, and global dance influences.
-
B.
The Turning Point
The Turning Point is a 1977 American drama film about the world of professional ballet, noted for its performances by Shirley MacLaine, Anne Bancroft, and Mikhail Baryshnikov.
-
C.
The Turning Point
The Turning Point is a notable work by James Mitchell, likely recognized as one of his significant literary or creative contributions.
-
D.
The Mustering
The Mustering is the English-titled installment of the fantasy series "The Exile," likely depicting a pivotal gathering or preparation for conflict within its narrative world.
-
E.
The Turning
The Turning is a 2020 supernatural horror film loosely based on Henry James's novella "The Turn of the Screw," following a governess who encounters disturbing forces while caring for two orphaned children in a mysterious estate.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb07ad3f48190a2173e42c5cfedb1 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f77f92224c8190b66adef1291cd47f |
completed | May 3, 2026, 5:02 p.m. |
| NEDg | Description generation | batch_69f780ccf5948190b374514370f910f4 |
completed | May 3, 2026, 5:07 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78157b9cc8190a1855cb9715aa7d5 |
completed | May 3, 2026, 5:09 p.m. |
Created at: April 9, 2026, 9:49 p.m.