Triple
T36545769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckleberry Ferry |
E901135
|
entity |
| Predicate | travelDestinationTo |
P21947
|
FINISHED |
| Object | Buckland |
—
|
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: Buckland | Statement: [Buckleberry Ferry, travelDestinationTo, Buckland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelDestinationTo Context triple: [Buckleberry Ferry, travelDestinationTo, Buckland]
-
A.
travelDestinationFrom
Indicates that a particular place serves as the destination reached when traveling from a specified origin location.
-
B.
journeyDestination
chosen
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
C.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
D.
travelDescriptor
Indicates how an instance of travel is characterized, such as by its mode, conditions, style, or other descriptive attributes of the journey.
-
E.
travelZone
Indicates a relationship where an entity is located in, moves within, or is permitted to move within a specified geographic or regulatory area.
- 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_69f76e61217081908b79d610fe67b013 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:11 p.m.