Triple
T3860137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Travels with Charley: In Search of America |
E90113
|
entity |
| Predicate | describesJourneyType |
P24304
|
FINISHED |
| Object | cross-country road trip |
—
|
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: cross-country road trip | Statement: [Travels with Charley: In Search of America, describesJourneyType, cross-country road trip]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describesJourneyType Context triple: [Travels with Charley: In Search of America, describesJourneyType, cross-country road trip]
-
A.
voyageType
chosen
Indicates the specific category or nature of a journey or trip that an entity undertakes.
-
B.
containsRideType
Indicates that one entity includes or offers a specific type or category of ride as part of its available options.
-
C.
typicalJourneyPurpose
Indicates the usual or most common reason or objective for which an entity undertakes a journey.
-
D.
offersClassOfTravel
Indicates that a service provider makes a particular class or tier of travel (e.g., economy, business, first) available as an option.
-
E.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec212a1c8190aba6311630c3fd3e |
completed | March 9, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69aee752c8a48190a670f73ed0bf1e61 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.