Triple
T19643649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oort constant A |
E471607
|
entity |
| Predicate | typicalValueApprox |
P99172
|
FINISHED |
| Object | 15 km/s/kpc |
—
|
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: 15 km/s/kpc | Statement: [Oort constant A, typicalValueApprox, 15 km/s/kpc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalValueApprox Context triple: [Oort constant A, typicalValueApprox, 15 km/s/kpc]
-
A.
typicalValueFor
chosen
Indicates that one entity represents a standard, representative, or commonly occurring value associated with another entity.
-
B.
approximateEstimation
Indicates an estimation relationship where one value or assessment is only roughly or closely, but not exactly, equal to another.
-
C.
approximationType
Indicates the specific method or scheme used to approximate a value, function, or relationship in a given context.
-
D.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
-
E.
typicalMeasure
Indicates the standard or characteristic quantitative measure typically associated with something, such as its usual size, weight, duration, or other magnitude.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641239ca08190a8bb8854f21ab562 |
completed | April 20, 2026, 3:07 p.m. |
| PD | Predicate disambiguation | batch_69e514e941008190898d978d7bde91e4 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.