Triple
T36545768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buckleberry Ferry |
E901135
|
entity |
| Predicate | travelDestinationFrom |
P187093
|
FINISHED |
| Object | The Shire |
—
|
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: The Shire | Statement: [Buckleberry Ferry, travelDestinationFrom, The Shire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelDestinationFrom Context triple: [Buckleberry Ferry, travelDestinationFrom, The Shire]
-
A.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
B.
travelDescriptor
Indicates how an instance of travel is characterized, such as by its mode, conditions, style, or other descriptive attributes of the journey.
-
C.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
D.
travelRouteContext
Indicates the contextual details (such as purpose, conditions, or circumstances) under which a particular travel route is taken or defined.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
- 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_69f76e61217081908b79d610fe67b013 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
| PDg | Predicate description generation | batch_69fb3424724c8190ba55ecf66fa0b171 |
completed | May 6, 2026, 12:29 p.m. |
Created at: May 3, 2026, 4:11 p.m.