Triple
T5272733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | YV |
E119297
|
entity |
| Predicate | disambiguates |
P56163
|
FINISHED |
| Object | Mesa Airlines from other airlines in booking systems |
—
|
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: Mesa Airlines from other airlines in booking systems | Statement: [YV, disambiguates, Mesa Airlines from other airlines in booking systems]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disambiguates Context triple: [YV, disambiguates, Mesa Airlines from other airlines in booking systems]
-
A.
resolves
Indicates that one entity successfully finds a solution, answer, or outcome for a problem, conflict, or uncertainty involving another entity.
-
B.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
C.
languageAmbiguity
Indicates that the meaning, interpretation, or reference of a linguistic expression is unclear or can be understood in multiple ways.
-
D.
hasDisambiguationPage
Indicates that there exists a disambiguation page used to distinguish between multiple entities or meanings associated with the same term.
-
E.
clarifiesThat
chosen
Indicates that one entity explains or makes another entity more understandable by removing ambiguity or confusion about it.
- 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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7d5a23908190a24e79d1b29d6fcf |
completed | March 20, 2026, 5:01 p.m. |
| PD | Predicate disambiguation | batch_69bd77c71268819094f9f5203eed392d |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:51 p.m.