Triple
T8016847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariot Arbuthnot |
E186638
|
entity |
| Predicate | hasPartInHisLife |
P74692
|
FINISHED |
| Object | administration of Nova Scotia during the American Revolutionary War |
—
|
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: administration of Nova Scotia during the American Revolutionary War | Statement: [Mariot Arbuthnot, hasPartInHisLife, administration of Nova Scotia during the American Revolutionary War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartInHisLife Context triple: [Mariot Arbuthnot, hasPartInHisLife, administration of Nova Scotia during the American Revolutionary War]
-
A.
hasPersonalLife
Indicates that an entity has aspects, activities, or relationships belonging to its private or non-professional life.
-
B.
hasPartInBiography
Indicates that a person or entity is featured or plays a role within someone’s biographical account.
-
C.
hasPartInHisHonor
Indicates that something includes or contains a part, section, or component that is dedicated or named in honor of a particular person.
-
D.
livedBefore
Indicates that one entity existed or was alive at an earlier time than another entity.
-
E.
hasBeenInvolvedIn
chosen
Indicates that an entity has participated in, taken part in, or been connected to a particular event, activity, or situation.
- 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_69ca82ac7fc081909b1398cf025423af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3df4f1b8819089a8b67f136bce9a |
completed | March 31, 2026, 3:22 a.m. |
| PD | Predicate disambiguation | batch_69cb048c9f488190b4fb8917a9c21bc5 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:20 p.m.