Triple
T1640449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malcolm Butler |
E35456
|
entity |
| Predicate | positionGroup |
P29748
|
FINISHED |
| Object | defensive back |
—
|
LITERAL 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: defensive back | Statement: [Malcolm Butler, positionGroup, defensive back]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionGroup Context triple: [Malcolm Butler, positionGroup, defensive back]
-
A.
positionClass
Indicates the classification or category assigned to an entity based on its role, rank, or position within a defined structure or system.
-
B.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
C.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
D.
positionA
Indicates the spatial or ordered position of an entity A within a defined reference frame or sequence.
-
E.
positioning
Indicates the spatial or contextual arrangement of one entity relative to another or within a given environment.
- F. None of above. chosen
Provenance (4 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a919306fd48190a245fc95e0e759d9 |
completed | March 5, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69a907cc9d348190b76b0d3f596e5a81 |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a9192f975c8190bfd514a4b5a8786c |
completed | March 5, 2026, 5:48 a.m. |
Created at: March 4, 2026, 7:28 p.m.