Triple
T27450457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 23 |
E692423
|
entity |
| Predicate | hasNumberingFormat |
P181640
|
FINISHED |
| Object | two-digit number without degree symbol |
—
|
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: two-digit number without degree symbol | Statement: [Runway 23, hasNumberingFormat, two-digit number without degree symbol]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberingFormat Context triple: [Runway 23, hasNumberingFormat, two-digit number without degree symbol]
-
A.
hasNumberingRole
Indicates that an entity holds a specific role or responsibility related to assigning, managing, or using numbers within a given context.
-
B.
hasNumberingIncrement
Indicates that one entity specifies the step size or increment used when numbering another entity in a sequence.
-
C.
hasNumberingWithin
Indicates that one entity assigns or follows a specific numbering scheme within the scope or structure of another entity.
-
D.
hasNumberingComputation
Indicates that an entity is associated with a process or method used to compute or determine its numbering.
-
E.
hasNumberingStart
Indicates that an ordered sequence or list begins at a specified starting number or position.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f7805c25dc8190b9977c561ba15975 |
completed | May 3, 2026, 5:05 p.m. |
Created at: April 27, 2026, 12:47 p.m.