Triple
T10288351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martha Reeves |
E241294
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Quicksand |
E298295
|
NE FINISHED |
How this triple was built (2 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: Quicksand | Statement: [Martha Reeves, notableWork, Quicksand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quicksand Context triple: [Martha Reeves, notableWork, Quicksand]
-
A.
Quicksand
chosen
"Quicksand" is a 1963 Motown soul single by Martha and the Vandellas, known for its driving beat and passionate vocals characteristic of the group's early hits.
-
B.
Quicksand
Quicksand is an influential American post-hardcore band known for its heavy, melodic sound and role in shaping 1990s alternative rock.
-
C.
Quicksand
Quicksand is a song by Icelandic musician Björk from her emotionally charged 2015 album "Vulnicura."
-
D.
Quicksand
"Quicksand" is a 1928 novel by Nella Larsen that explores race, identity, and gender through the experiences of a mixed-race woman navigating Black and white societies in the early 20th-century United States and Denmark.
-
E.
Mud
Mud is a 2012 American drama film directed by Jeff Nichols, in which Matthew McConaughey plays a fugitive who befriends two boys on the Mississippi River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b9d76c8190b1ef6ecf4c1a2a09 |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f8556f4081908390bc5c14dcf560 |
completed | April 9, 2026, 12:52 a.m. |
Created at: April 6, 2026, 11:41 a.m.