Triple
T17182273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schmitz |
E417012
|
entity |
| Predicate | numberOfArsonistsInGroup |
P36179
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Schmitz, numberOfArsonistsInGroup, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfArsonistsInGroup Context triple: [Schmitz, numberOfArsonistsInGroup, 2]
-
A.
numberOfPerpetrators
chosen
Indicates the count of distinct individuals who carried out or participated in a particular act, event, or offense.
-
B.
armedGroup
Indicates that an entity is an organized group equipped with weapons and capable of using armed force.
-
C.
numberOfPeopleAccused
Indicates the count of individuals who are formally alleged to have committed a particular act or offense.
-
D.
hasNumberOfAssailants
Indicates the relationship specifying how many assailants are involved in a given event or situation.
-
E.
armedGroupInvolved
Indicates that an armed group participated in, contributed to, or was otherwise involved in 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42d934ec08190acc47073758ac3c0 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:37 a.m.