Triple
T28537812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2U |
E722212
|
entity |
| Predicate | airlineMarketFocus |
P55881
|
FINISHED |
| Object | Israeli outbound leisure market |
—
|
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: Israeli outbound leisure market | Statement: [2U, airlineMarketFocus, Israeli outbound leisure market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineMarketFocus Context triple: [2U, airlineMarketFocus, Israeli outbound leisure market]
-
A.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
-
B.
airlineMarket
Indicates a commercial air transport relationship where an airline provides or operates flight services within a specific origin–destination market or route.
-
C.
airlineMarketPosition
Indicates the competitive standing or role an airline holds within a specific market or route network.
-
D.
airlineMarketImpact
Indicates the effect that an airline’s operations, strategies, or presence have on the overall conditions and dynamics of a specific air travel market.
-
E.
airlineMarketSegment
chosen
Indicates a relationship where an airline is associated with a specific market segment it targets or operates within (e.g., business, leisure, regional).
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f66d7765208190b87b1cc6d96a151c |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f66abfdaf08190a55f14c70be6fd4d |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 3:33 a.m.