Triple
T27384106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 34 |
E691317
|
entity |
| Predicate | numberDerivedFrom |
P197976
|
FINISHED |
| Object | magnetic azimuth divided by 10 |
—
|
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: magnetic azimuth divided by 10 | Statement: [Runway 34, numberDerivedFrom, magnetic azimuth divided by 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberDerivedFrom Context triple: [Runway 34, numberDerivedFrom, magnetic azimuth divided by 10]
-
A.
numberDescribedAs
Indicates that a number is characterized, labeled, or referred to using a particular description or phrase.
-
B.
number
Indicates that one entity is associated with a specific numerical value or count in relation to another entity or context.
-
C.
numberVariedBetween
Indicates that the numerical value associated with an entity changed across a specified range between two points or over a given period.
-
D.
numberReferenced
Indicates that one entity refers to or cites a specific number associated with another entity.
-
E.
isNumberedBy
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
- 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_69ef520386788190bc92cfcd97ebb67a |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fec00f27988190955de6b6348a4d97 |
completed | May 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69febd52037c8190b475dbd50fdbc13e |
completed | May 9, 2026, 4:51 a.m. |
| PDg | Predicate description generation | batch_69fec00e5c1c819083d174bb4bc35f29 |
completed | May 9, 2026, 5:03 a.m. |
Created at: April 27, 2026, 12:23 p.m.