Triple
T724004
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franconian Jerusalem |
E14680
|
entity |
| Predicate | nicknameReason |
P7596
|
FINISHED |
| Object | large Jewish population in Fürth |
—
|
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: large Jewish population in Fürth | Statement: [Franconian Jerusalem, nicknameReason, large Jewish population in Fürth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nicknameReason Context triple: [Franconian Jerusalem, nicknameReason, large Jewish population in Fürth]
-
A.
reasonForNickname
chosen
Indicates the explanation or cause behind why a particular nickname was given to an entity.
-
B.
reasonForName
Indicates the explanation or cause behind why an entity has a particular name.
-
C.
nameChangeReason
Indicates the reason or justification for a change in an entity’s name.
-
D.
reasonForEpithet
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
-
E.
localNickname
Indicates that an entity is known by a particular nickname within a specific local or regional context.
- 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a6ab508190b70a05a9d77829a5 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.