Triple
T23321413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolf Schrömgens |
E591160
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Trivago |
—
|
NE NERFINISHED |
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: Trivago | Statement: [Rolf Schrömgens, employer, Trivago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trivago Context triple: [Rolf Schrömgens, employer, Trivago]
-
A.
Orbitz
Orbitz is a major online travel agency that allows users to search for and book flights, hotels, rental cars, and vacation packages.
-
B.
trivago
chosen
trivago is a global hotel and accommodation metasearch platform that compares prices from numerous booking sites to help users find and book lodging deals.
-
C.
Booking.com
Booking.com is a major global online travel agency that allows users to search for and book accommodations such as hotels, apartments, and vacation rentals.
-
D.
Agoda
Agoda is a global online travel agency known for offering hotel and accommodation bookings, flights, and travel services, particularly strong in the Asia-Pacific region.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f19785ae5481908816b37da95ceb3e |
completed | April 29, 2026, 5:30 a.m. |
Created at: April 17, 2026, 5:07 p.m.