Triple
T31862575
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Strawberries Oceans Ships Forest |
E813370
|
entity |
| Predicate | usesSamplesFrom |
P118139
|
FINISHED |
| Object | Off the Ground |
—
|
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: Off the Ground | Statement: [Strawberries Oceans Ships Forest, usesSamplesFrom, Off the Ground]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSamplesFrom Context triple: [Strawberries Oceans Ships Forest, usesSamplesFrom, Off the Ground]
-
A.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
B.
featuresSamplesFrom
chosen
Indicates that one entity includes or incorporates sample elements originating from another entity.
-
C.
basedOnSampleOf
Indicates that something is derived, inferred, or constructed from a particular sample or subset of data rather than from the entire population.
-
D.
extantSamples
Indicates that there exist currently surviving or available samples associated with the given entity or context.
-
E.
usesSamplingOrInterpolation
Indicates that one entity applies sampling or interpolation techniques to obtain or approximate values from another entity or dataset.
- 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_69f348ebf32881908d9439646933dc76 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 30, 2026, 11:53 p.m.