Triple
T35375366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ma_MISS spectrometer |
E1021892
|
entity |
| Predicate | miniaturized |
P107379
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ma_MISS spectrometer, miniaturized, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: miniaturized Context triple: [Ma_MISS spectrometer, miniaturized, true]
-
A.
miniaturizedIn
Indicates that one entity exists as a smaller-scale or reduced-size version within or relative to another entity.
-
B.
miniaturizedBy
chosen
Indicates that an entity has been made smaller in size or scale by another entity or process.
-
C.
hasMiniature
Indicates that one entity possesses or includes a smaller-scale representation or model of another entity.
-
D.
diameterMini
Indicates that one entity is the minimum diameter measurement associated with another entity.
-
E.
minimality
Indicates that something has the smallest or least possible value, size, or complexity among a relevant set, such that no strictly smaller or simpler alternative satisfies the same conditions.
- 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_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.