Triple
T17932093
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lastminute.com |
E448356
|
entity |
| Predicate | competitor |
P1375
|
FINISHED |
| Object | Travelocity |
E308297
|
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: Travelocity | Statement: [Lastminute.com, competitor, Travelocity]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Travelocity Context triple: [Lastminute.com, competitor, Travelocity]
-
A.
Travelocity
chosen
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.
Orbitz
Orbitz is a major online travel agency that allows users to search for and book flights, hotels, rental cars, and vacation packages.
-
C.
Priceline
Priceline is a major online travel agency known for offering discounted rates on flights, hotels, rental cars, and vacation packages.
-
D.
Expedia Group
Expedia Group is a leading American online travel and technology company that operates numerous global travel fare aggregators and travel metasearch engines.
-
E.
Travelport
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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a552bb848190871251474cc208d5 |
completed | April 19, 2026, 9:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03290f30a88190814f4045eb31e639 |
completed | May 12, 2026, 1:20 p.m. |
Created at: April 10, 2026, 10:20 a.m.