Triple
T4220235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AFR |
E94319
|
entity |
| Predicate | hasCallsignPrefixRole |
P55388
|
FINISHED |
| Object | prefix for Air France radio callsigns |
—
|
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: prefix for Air France radio callsigns | Statement: [AFR, hasCallsignPrefixRole, prefix for Air France radio callsigns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCallsignPrefixRole Context triple: [AFR, hasCallsignPrefixRole, prefix for Air France radio callsigns]
-
A.
hasCallsignCompanion
Indicates that one entity serves as a companion or associated partner to another entity’s callsign.
-
B.
callsign
Indicates that an entity is assigned or uses a specific radio or identification callsign as its designated identifier in communication contexts.
-
C.
supportsCallSign
Indicates that one entity is capable of recognizing, handling, or operating using a specified call sign.
-
D.
formerCallSign
Indicates that one identifier was previously used as the call sign for the other entity before being changed or replaced.
-
E.
callsignSeries
Indicates that one entity is a member or installment within a series or sequence that shares the same callsign.
- 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_69b3451997e08190851db4a9a588837d |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69b347f1d7b48190bd8974c03c7dc937 |
completed | March 12, 2026, 11:10 p.m. |
| PDg | Predicate description generation | batch_69b34e4ace648190acf911853d4fcf86 |
completed | March 12, 2026, 11:37 p.m. |
Created at: March 12, 2026, 11:04 p.m.