Triple
T23323954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Dunne |
E591235
|
entity |
| Predicate | roadTripDestination |
P21947
|
FINISHED |
| Object | Aspen, Colorado |
—
|
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: Aspen, Colorado | Statement: [Harry Dunne, roadTripDestination, Aspen, Colorado]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadTripDestination Context triple: [Harry Dunne, roadTripDestination, Aspen, Colorado]
-
A.
journeyDestination
chosen
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
B.
travelRouteContext
Indicates the contextual details (such as purpose, conditions, or circumstances) under which a particular travel route is taken or defined.
-
C.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
D.
travelRouteOf
Indicates the path or itinerary that an entity follows or uses when traveling from one location to another.
-
E.
notableDestination
Indicates that a location is recognized as a significant or prominent place that people commonly travel to or aim to visit.
- 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1978731b0819090f92ef768f2a749 |
completed | April 29, 2026, 5:30 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:08 p.m.