Triple
T7233165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Tippecanoe |
E154950
|
entity |
| Predicate | hasAssociatedDeathCause |
P144
|
FINISHED |
| Object | pneumonia (of William Henry Harrison) |
—
|
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: pneumonia (of William Henry Harrison) | Statement: [Old Tippecanoe, hasAssociatedDeathCause, pneumonia (of William Henry Harrison)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedDeathCause Context triple: [Old Tippecanoe, hasAssociatedDeathCause, pneumonia (of William Henry Harrison)]
-
A.
associatedWithDeathOf
Indicates a relationship where one entity is connected in some relevant way to the death of another entity, such as by involvement, causation, or contextual association.
-
B.
causeOfDeath
chosen
Indicates the specific factor, event, or condition that directly resulted in an entity’s death.
-
C.
hasMannerOfDeath
Indicates the specific way or circumstances in which an entity died, such as natural causes, accident, homicide, or suicide.
-
D.
hasMannerOfDeathOfVictim
Indicates the specific way or circumstances in which the victim died in relation to the event or action being described.
-
E.
reasonForDeath
Indicates the cause, circumstance, or condition that led to an entity’s death.
- 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_69c68811dd1c8190ac460bb39e64e1f0 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea552a688190a00f5d0ad982f787 |
completed | March 27, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69c6e7644648819096a5e2de5d0dbe97 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:55 p.m.