Triple
T38497256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Bartram |
E919726
|
entity |
| Predicate | traveledIn |
P192472
|
FINISHED |
| Object | North Carolina |
—
|
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: North Carolina | Statement: [William Bartram, traveledIn, North Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traveledIn Context triple: [William Bartram, traveledIn, North Carolina]
-
A.
traveledAs
Indicates that an entity moved from one place to another in the role, capacity, or identity specified by another entity (e.g., as a tourist, as a representative, as a refugee).
-
B.
travelsOn
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.
journeyedWith
Indicates that one entity traveled or went on a journey together with another entity as companions.
-
E.
traveledToBy
Indicates that an entity has been traveled to or visited by another entity.
- 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_69f76e9ddd4481908f8c04439d848f9d |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd0b92f42881908cd77e3f058adcc2 |
completed | May 7, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69fd0a3d68d4819094d92040f7c48d7c |
completed | May 7, 2026, 9:55 p.m. |
| PDg | Predicate description generation | batch_69fd0b92150881909b1166fe6d09aa19 |
completed | May 7, 2026, 10 p.m. |
Created at: May 3, 2026, 4:31 p.m.