Triple
T37142487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nan Dungortheb |
E920151
|
entity |
| Predicate | travelThrough |
P54144
|
FINISHED |
| Object | rarely attempted |
—
|
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: rarely attempted | Statement: [Nan Dungortheb, travelThrough, rarely attempted]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelThrough Context triple: [Nan Dungortheb, travelThrough, rarely attempted]
-
A.
travelsThrough
chosen
Indicates that something moves along, passes across, or is routed via a particular path, medium, or location.
-
B.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
C.
tourWith
Indicates that one entity accompanies another on a tour, sharing the same itinerary or guided experience.
-
D.
travelRouteOf
Indicates the path or itinerary that an entity follows or uses when traveling from one location to another.
-
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_69f76e9e9d008190a250b0387c992c74 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:15 p.m.