Triple
T33925849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolly |
E869747
|
entity |
| Predicate | associatedWithMotelJourney |
P206740
|
FINISHED |
| Object | cross-country trip in the United States |
—
|
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 trip in the United States | Statement: [Dolly, associatedWithMotelJourney, cross-country trip in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithMotelJourney Context triple: [Dolly, associatedWithMotelJourney, cross-country trip in the United States]
-
A.
journeyedWith
Indicates that one entity traveled or went on a journey together with another entity as companions.
-
B.
associatedWithReservation
Indicates that one entity has a connection or linkage to a specific reservation.
-
C.
associatedHotel
Indicates that there is a relationship linking an entity to a specific hotel with which it is connected or affiliated.
-
D.
reservationLocatedAlong
Indicates that a reservation is situated along, adjacent to, or following the course or extent of a specified linear feature such as a road, river, or boundary.
-
E.
associatedWithFlightsAt
Indicates a relationship where something is connected or linked to specific flights occurring at a particular location or time.
- F. None of above. chosen
Provenance (4 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_69f349992c508190aa4afa24a086cc8c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037e07fe4481909ca21eae7a941ee7 |
completed | May 12, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:49 a.m.