Triple
T37209196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rain |
E922252
|
entity |
| Predicate | nearlyKilledBy |
P83313
|
FINISHED |
| Object | U.S. Cavalry |
—
|
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: U.S. Cavalry | Statement: [Rain, nearlyKilledBy, U.S. Cavalry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearlyKilledBy Context triple: [Rain, nearlyKilledBy, U.S. Cavalry]
-
A.
killedNear
Indicates that one entity killed another in close spatial proximity to a specified location or reference point.
-
B.
nearlyDiesFrom
chosen
Indicates that an entity comes very close to dying as a result of another entity or event, but ultimately survives.
-
C.
killedOnGround
Indicates that one entity caused the death of another entity while the victim was on the ground.
-
D.
killedOrMortallyWounded
Indicates that one entity caused the death of, or inflicted injuries certain to result in the death of, another entity.
-
E.
killsOrIsKilledBy
Indicates that one entity causes the death of the other or is itself killed by that entity, capturing a mutual or directional lethal relationship between them.
- 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_69f76ea4849481909b4a3073efb0114c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55de3b9c8190a7656aeab3c3ffbc |
completed | May 6, 2026, 2:53 p.m. |
| PD | Predicate disambiguation | batch_69fb35bc92e08190bff447624e2df791 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.