Triple
T86072
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benito Mussolini |
E1730
|
entity |
| Predicate | workedAs |
P4325
|
FINISHED |
| Object | schoolteacher |
—
|
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: schoolteacher | Statement: [Benito Mussolini, workedAs, schoolteacher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedAs Context triple: [Benito Mussolini, workedAs, schoolteacher]
-
A.
workedUnder
Indicates that one entity was hierarchically subordinate to and performed work under the supervision or authority of another entity.
-
B.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
-
C.
associatedWork
Indicates that there exists a related or connected work (such as a publication, creative piece, or project) that is meaningfully linked to the subject.
-
D.
formerEmployer
Indicates that one entity previously employed the other but no longer does so.
-
E.
hadOccupationStatusUntil
Indicates that an entity held a particular occupational status up to, but not necessarily beyond, a specified point in time.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a250e401288190ba12322c9c5f07c9 |
completed | Feb. 28, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69a24eb59e808190811c20518f39b1cc |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a250e2a80881909e5a653260e6f8e0 |
completed | Feb. 28, 2026, 2:20 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.