Triple
T38033140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erfurt Cathedral |
E948970
|
entity |
| Predicate | Gloriosa |
P189883
|
FINISHED |
| Object | largest medieval free-swinging bell in the world |
—
|
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: largest medieval free-swinging bell in the world | Statement: [Erfurt Cathedral, Gloriosa, largest medieval free-swinging bell in the world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Gloriosa Context triple: [Erfurt Cathedral, Gloriosa, largest medieval free-swinging bell in the world]
-
A.
Bloom
Indicates the process or state of a plant or similar organism producing and displaying flowers.
-
B.
الغطاء النباتي
Indicates the presence, extent, or characteristics of plant cover in a given area.
-
C.
التيجان والأوسمة
Indicates the relationship of conferring, wearing, or possessing crowns and decorations (such as medals or orders of honor) as marks of rank, distinction, or recognition.
-
D.
Mawtini
Indicates a relationship of national belonging or patriotic connection, often expressing devotion or attachment to one’s homeland.
-
E.
Diva
Indicates that an entity is characterized as a celebrated but temperamental performer, often demanding special treatment or attention in their professional context.
- 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_69f76efd1bc48190a729097fe5177b61 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fc44c7e73c819082d4fc1900fb9632 |
completed | May 7, 2026, 7:52 a.m. |
| PD | Predicate disambiguation | batch_69fbc8efffbc8190a139798ad1880526 |
completed | May 6, 2026, 11:04 p.m. |
| PDg | Predicate description generation | batch_69fc44c67118819088accfeded7b449e |
completed | May 7, 2026, 7:52 a.m. |
Created at: May 3, 2026, 4:20 p.m.