Triple
T13834141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandy Hook Elementary School |
E332479
|
entity |
| Predicate | numberOfChildVictimsIn2012Shooting |
P71968
|
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: [Sandy Hook Elementary School, numberOfChildVictimsIn2012Shooting, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfChildVictimsIn2012Shooting Context triple: [Sandy Hook Elementary School, numberOfChildVictimsIn2012Shooting, 20]
-
A.
childrenKilledBy
Indicates that the children of a given entity were killed by another specified entity or agent.
-
B.
numberOfPeopleShot
Indicates the count of individuals who were shot in a particular event or context.
-
C.
numberOfAdultVictimsKilled
Indicates the total count of adult victims who were killed in the described event or incident.
-
D.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
E.
numberOfChildrenMurdered
chosen
Indicates the count of children who have been killed in an act of murder.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de029a34bc8190ae892ef7b09fc9e9 |
completed | April 14, 2026, 9:02 a.m. |
| PD | Predicate disambiguation | batch_69dbc86668e08190ba9135d1c3f38d35 |
completed | April 12, 2026, 4:29 p.m. |
Created at: April 9, 2026, 10:13 p.m.