Triple
T12032433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Distribution Systems |
E286444
|
entity |
| Predicate | hasMajorExample |
P58835
|
FINISHED |
| Object | Worldspan |
E697626
|
NE 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: Worldspan | Statement: [Global Distribution Systems, hasMajorExample, Worldspan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Worldspan Context triple: [Global Distribution Systems, hasMajorExample, Worldspan]
-
A.
Travelocity
Travelocity is a major online travel agency that allows users to search for and book flights, hotels, rental cars, vacation packages, and other travel services.
-
B.
Wotif Group
Wotif Group is an online travel company best known for its hotel and accommodation booking platforms, particularly in the Australian and Asia-Pacific markets.
-
C.
Priceline
Priceline is a major online travel agency known for offering discounted rates on flights, hotels, rental cars, and vacation packages.
-
D.
Hotels.com
Hotels.com is a major online travel agency specializing in hotel and accommodation reservations worldwide.
-
E.
Travelport
chosen
Travelport is a global travel technology company that provides distribution, payment, and retailing solutions connecting travel agencies, airlines, hotels, and other travel suppliers.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915124e4c8190b0264c2a09e3c2f3 |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d6ec4b8819093ff50254a851444 |
completed | May 1, 2026, 12:32 p.m. |
Created at: April 8, 2026, 9:47 p.m.