Triple
T3731400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 4L/22R |
E79070
|
entity |
| Predicate | isNumberedAccordingTo |
P37553
|
FINISHED |
| Object | magnetic azimuth of runway centerline |
—
|
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 of runway centerline | Statement: [Runway 4L/22R, isNumberedAccordingTo, magnetic azimuth of runway centerline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNumberedAccordingTo Context triple: [Runway 4L/22R, isNumberedAccordingTo, magnetic azimuth of runway centerline]
-
A.
isNumbered
Indicates that an entity has been assigned a specific number or position in an ordered sequence.
-
B.
isNumberedBy
chosen
Indicates that an entity is assigned, identified, or organized by a specific number or numbering scheme.
-
C.
isSectionNumber
Indicates that one entity is the section number identifier associated with another entity, typically within a structured document or text.
-
D.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
E.
usesHarmonizedNumberingWith
Indicates that two entities apply the same standardized numbering scheme so their identifiers or codes are directly comparable or aligned.
- 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_69ad8b0e4650819090ad7cef094285e8 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb21002c81908438170ed6f6c271 |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc04746588190b0dc535638f23546 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.