Triple
T300747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wilkes Booth |
E6191
|
entity |
| Predicate | fledFrom |
P11257
|
FINISHED |
| Object | Ford's Theatre after shooting Abraham Lincoln |
—
|
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: Ford's Theatre after shooting Abraham Lincoln | Statement: [John Wilkes Booth, fledFrom, Ford's Theatre after shooting Abraham Lincoln]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fledFrom Context triple: [John Wilkes Booth, fledFrom, Ford's Theatre after shooting Abraham Lincoln]
-
A.
leasedFrom
Indicates that one entity is renting or leasing something from another entity, which acts as the owner or lessor.
-
B.
relocatedFrom
Indicates that an entity has moved or been transferred away from a specified original location.
-
C.
lastFlight
Indicates that one flight is the final or most recent flight taken or operated by a given entity within a specified context or sequence.
-
D.
hadFort
Indicates that an entity possessed, controlled, or contained a fort at some time.
-
E.
lostTo
Indicates that one entity was defeated by another in a competition, conflict, or comparison.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2af1388190b93235602ace679e |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.