Triple
T35375420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOMA mass spectrometer |
E1021893
|
entity |
| Predicate | receivesSamplesFrom |
P110259
|
FINISHED |
| Object | Rosalind Franklin rover drill |
—
|
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: Rosalind Franklin rover drill | Statement: [MOMA mass spectrometer, receivesSamplesFrom, Rosalind Franklin rover drill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receivesSamplesFrom Context triple: [MOMA mass spectrometer, receivesSamplesFrom, Rosalind Franklin rover drill]
-
A.
samplingSource
chosen
Indicates that one entity serves as the origin or provider from which another entity is sampled or drawn.
-
B.
hearsFrom
Indicates that one entity receives information, communication, or a message from another entity.
-
C.
featuresSamplesFrom
Indicates that one entity includes or incorporates sample elements originating from another entity.
-
D.
receives
Indicates that one entity is the recipient of something (such as an object, message, or action) from another entity.
-
E.
hasSampling
Indicates that one entity performs, involves, or is associated with the act or process of sampling in relation to another 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:03 p.m.