Triple
T37094164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Beckett |
E918511
|
entity |
| Predicate | travelsUsing |
P15183
|
FINISHED |
| Object | sliding technology |
—
|
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: sliding technology | Statement: [Maggie Beckett, travelsUsing, sliding technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelsUsing Context triple: [Maggie Beckett, travelsUsing, sliding technology]
-
A.
travelsFor
Indicates that one entity moves from place to place on behalf of, or for the benefit or purpose of, another entity or objective.
-
B.
travelsOn
chosen
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
C.
travelsThrough
Indicates that something moves along, passes across, or is routed via a particular path, medium, or location.
-
D.
coTraveler
Indicates that two or more entities are traveling together along (part of) the same journey or route.
-
E.
travelRouteContext
Indicates the contextual details (such as purpose, conditions, or circumstances) under which a particular travel route is taken or defined.
- 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_69f76e9a48bc8190a3947508d8bca408 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: May 3, 2026, 4:14 p.m.