Triple
T18122021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chowchilla school bus kidnapping |
E433762
|
entity |
| Predicate | numberOfAdultVictims |
P130531
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [Chowchilla school bus kidnapping, numberOfAdultVictims, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfAdultVictims Context triple: [Chowchilla school bus kidnapping, numberOfAdultVictims, 1]
-
A.
numberOfAdultVictimsKilled
Indicates the total count of adult victims who were killed in the described event or incident.
-
B.
numberOfVictimsConfirmed
Indicates the confirmed count of victims associated with an event, incident, or situation.
-
C.
numberOfVictimsClaimed
Indicates the reported count of victims associated with a particular event, incident, or action.
-
D.
numberOfVictimsInjured
Indicates the count of victims who sustained injuries as a result of the event or incident.
-
E.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
- 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddeb2d7881909326cb9d2f5e2fb5 |
completed | April 19, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_69e43313ca788190baa224269e71de49 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:28 a.m.