Triple
T13309804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbine High School massacre |
E317029
|
entity |
| Predicate | numberOfGunshotWoundsVictims |
P66678
|
FINISHED |
| Object | 20+ |
—
|
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: 20+ | Statement: [Columbine High School massacre, numberOfGunshotWoundsVictims, 20+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGunshotWoundsVictims Context triple: [Columbine High School massacre, numberOfGunshotWoundsVictims, 20+]
-
A.
numberOfGunshotWounds
chosen
Indicates the count of gunshot wounds associated with a particular entity or event.
-
B.
numberOfVictimsInjured
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
C.
numberOfPeopleShot
Indicates the count of individuals who were shot in a particular event or context.
-
D.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
E.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
- 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_69d806b40ab4819094adf6c374f4811a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6893708190aeebf4c47386cff7 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:29 p.m.