Triple
T8208485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sword of Napoleon |
E191749
|
entity |
| Predicate | materialUseContext |
P25885
|
FINISHED |
| Object | state ceremonies |
—
|
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: state ceremonies | Statement: [Sword of Napoleon, materialUseContext, state ceremonies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materialUseContext Context triple: [Sword of Napoleon, materialUseContext, state ceremonies]
-
A.
commonMaterialContext
Indicates that two or more entities share a similar or related material composition, substance, or physical makeup.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
materialReusedAt
Indicates that some or all of a material is used again at a specified location or facility.
-
D.
materialProvidedFor
Indicates that one entity supplies or makes available a material for use, processing, or incorporation by another entity or purpose.
-
E.
materialInvolved
chosen
Indicates that a particular material participates in, is used by, or is otherwise involved in the referenced process, event, or relationship.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb726d26ec8190957da68227f5ce61 |
completed | March 31, 2026, 7:06 a.m. |
| PD | Predicate disambiguation | batch_69cb36ad01ac81909609b15f6a6c8581 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:43 p.m.