Triple
T15710745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanna Schmitz |
E380829
|
entity |
| Predicate | reasonForAcceptingResponsibility |
P24494
|
FINISHED |
| Object | to conceal illiteracy |
—
|
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: to conceal illiteracy | Statement: [Hanna Schmitz, reasonForAcceptingResponsibility, to conceal illiteracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForAcceptingResponsibility Context triple: [Hanna Schmitz, reasonForAcceptingResponsibility, to conceal illiteracy]
-
A.
reasonWritten
Indicates that one entity is the reason or motivation for which another entity was written or authored.
-
B.
statedReason
chosen
Indicates that one entity expresses or provides another entity as the explanation, justification, or motive for an action, event, or claim.
-
C.
apologizedFor
Indicates that one entity expressed regret or remorse to another entity specifically about a particular action, event, or wrongdoing.
-
D.
responsibleFor
Indicates that one entity has a duty, obligation, or role to manage, oversee, or be accountable for another entity or outcome.
-
E.
apologyIssuedBy
Indicates that an apology has been made by a specific entity as the source or initiator of that apology.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69e00526759c819088b80d85138b8974 |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:45 a.m.