Triple
T4119130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mach number |
E90366
|
entity |
| Predicate | lessThanOneMeaning |
P54384
|
FINISHED |
| Object | subsonic condition |
—
|
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: subsonic condition | Statement: [Mach number, lessThanOneMeaning, subsonic condition]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lessThanOneMeaning Context triple: [Mach number, lessThanOneMeaning, subsonic condition]
-
A.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
B.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
C.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
-
D.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
oneOfFew
Indicates that the subject is one member of a small, limited set of entities that share a specified property or role.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af0246e40081908ad6741a830ca68e |
completed | March 9, 2026, 5:24 p.m. |
| PD | Predicate disambiguation | batch_69af01867698819098e4144634b2ec4f |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af0245adbc81908b89a40850047975 |
completed | March 9, 2026, 5:24 p.m. |
Created at: March 9, 2026, 3:41 p.m.