Triple
T28910645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bebot (traditional Filipino elements) |
E733214
|
entity |
| Predicate | wasSampledIn |
P57982
|
FINISHED |
| Object | The Apl Song |
—
|
NE NERFINISHED |
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: The Apl Song | Statement: [Bebot (traditional Filipino elements), wasSampledIn, The Apl Song]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasSampledIn Context triple: [Bebot (traditional Filipino elements), wasSampledIn, The Apl Song]
-
A.
hasBeenSampledIn
chosen
Indicates that an entity has been selected or taken as a sample within a specified context, location, or dataset.
-
B.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
C.
workSampledBy
Indicates that a work (such as a song or recording) incorporates a portion of another work through sampling.
-
D.
hasSampling
Indicates that one entity performs, involves, or is associated with the act or process of sampling in relation to another entity.
-
E.
sampledDuringMission
Indicates that one entity was collected or sampled in the course of a specific mission involving the other entity.
- F. None of above.
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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65ade78ac8190a1b704cf9a097961 |
completed | May 2, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:11 a.m.