Triple
T4549771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mindelheim |
E110132
|
entity |
| Predicate | FrundsbergfestType |
P9865
|
FINISHED |
| Object | historical festival |
—
|
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: historical festival | Statement: [Mindelheim, FrundsbergfestType, historical festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: FrundsbergfestType Context triple: [Mindelheim, FrundsbergfestType, historical festival]
-
A.
fortType
Indicates the specific kind or classification of a fort associated with an entity.
-
B.
eraOfMainCastle
Indicates the historical period or era during which the main castle associated with an entity was built, used, or most prominent.
-
C.
feastType
chosen
Indicates the specific kind or category of feast associated with an event or occasion.
-
D.
feudalCenter
Indicates that a location serves as the primary seat of authority, administration, or power within a feudal system.
-
E.
FrenchSide
Indicates that an entity is positioned on, associated with, or belongs to the French side of a border, division, 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f3f8348190868e274ac4df87ce |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5223423c81908317351b58cff5f5 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.