Triple
T3360413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Mère de l’Empereur |
E70706
|
entity |
| Predicate | usedFromApprox |
P47571
|
FINISHED |
| Object | 1804 |
—
|
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: 1804 | Statement: [Madame Mère de l’Empereur, usedFromApprox, 1804]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedFromApprox Context triple: [Madame Mère de l’Empereur, usedFromApprox, 1804]
-
A.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
B.
usedFor
Indicates that one entity serves a purpose, function, or role in accomplishing, enabling, or supporting another entity or activity.
-
C.
usedDataFrom
Indicates that one entity utilized or relied on data originating from another entity.
-
D.
usedToInfer
Indicates that one entity serves as a basis or source from which another entity is logically derived or concluded.
-
E.
approximates
Indicates that one entity is close to, but not exactly equal to, the value, form, or behavior of another entity.
- 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_69ad85a660c48190998489309a3b4869 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb267ec1081909a4e3e227d5bad01 |
completed | March 8, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69ada4317e288190ab7d0f66e9dba65f |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada698eeb48190a1f5762fdd3b7b63 |
completed | March 8, 2026, 4:40 p.m. |
Created at: March 8, 2026, 3:13 p.m.