Triple
T9113610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solomon Northup |
E218664
|
entity |
| Predicate | hasParticularNotableEvent |
P25528
|
FINISHED |
| Object | kidnapped into slavery in 1841 |
—
|
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: kidnapped into slavery in 1841 | Statement: [Solomon Northup, hasParticularNotableEvent, kidnapped into slavery in 1841]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularNotableEvent Context triple: [Solomon Northup, hasParticularNotableEvent, kidnapped into slavery in 1841]
-
A.
hasNamesakeNotableEvent
Indicates that one entity serves as the namesake for a notable event associated with the other entity.
-
B.
hasHistoricalEvent
Indicates that a historical event occurred in, is associated with, or is relevant to a particular entity.
-
C.
famousForEvent
chosen
Indicates that an entity is widely known or recognized specifically because of a particular event.
-
D.
notableSubevent
Indicates that one event is a particularly significant or noteworthy component within a larger, encompassing event.
-
E.
notableEventResponse
Indicates a response, reaction, or consequence that occurs as a result of a notable event.
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca84b0a048190964f560f78e27cce |
completed | April 1, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69cc65fe5be081909d4470d6317b14a6 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:16 p.m.