Triple
T6565527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christiania |
E153896
|
entity |
| Predicate | usedAsNameFrom |
P59337
|
FINISHED |
| Object | 17th century |
—
|
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: 17th century | Statement: [Christiania, usedAsNameFrom, 17th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsNameFrom Context triple: [Christiania, usedAsNameFrom, 17th century]
-
A.
usedAsNameSourceFor
Indicates that one entity serves as the origin or basis from which another entity’s name is derived.
-
B.
oftenUsedAsNameFor
Indicates that something frequently serves as a name or designation for another entity.
-
C.
nameUsedIn
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
-
D.
usesNameSince
chosen
Indicates that an entity has been using a particular name continuously starting from a specified point in time.
-
E.
usesNameDueTo
Indicates that one entity adopts or applies a particular name for another entity specifically because of some motivating reason, circumstance, or dependency.
- 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_69c6880cb35881909b763eb0125236b9 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6acf93cb48190b54f5dd6febd34dc |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:52 p.m.