Triple
T6435303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Concur Technologies |
E129879
|
entity |
| Predicate | product |
P490
|
FINISHED |
| Object | Concur Travel |
E129879
|
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: Concur Travel | Statement: [Concur Technologies, product, Concur Travel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Concur Travel Context triple: [Concur Technologies, product, Concur Travel]
-
A.
Concur Technologies
chosen
Concur Technologies is a software company best known for its cloud-based travel and expense management solutions used by businesses worldwide.
-
B.
Priceline
Priceline is a major online travel agency known for offering discounted rates on flights, hotels, rental cars, and vacation packages.
-
C.
Expedia Group
Expedia Group is a leading American online travel and technology company that operates numerous global travel fare aggregators and travel metasearch engines.
-
D.
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.
-
E.
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.
- 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_69c0084caac48190a7bc2ad8ba44536f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c069415c3c8190b91bd12ae79edd26 |
completed | March 22, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bbf31bc8190981362639a0e1ce5 |
completed | March 27, 2026, 9:19 a.m. |
Created at: March 22, 2026, 4:45 p.m.