Triple
T28547614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mainz Cathedral |
E722488
|
entity |
| Predicate | underwentFire |
P102908
|
FINISHED |
| Object | 1009 |
—
|
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: 1009 | Statement: [Mainz Cathedral, underwentFire, 1009]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underwentFire Context triple: [Mainz Cathedral, underwentFire, 1009]
-
A.
underFire
Indicates that an entity is being attacked, heavily criticized, or subjected to intense pressure by another entity or group.
-
B.
burnsWhen
Indicates that one entity causes another entity to ignite or combust when they come into contact or under specified conditions.
-
C.
destroyedByFire
Indicates that something has been ruined, damaged, or rendered unusable as a direct result of a fire.
-
D.
burnedDownIn
chosen
Indicates that a structure or object was destroyed by fire during a particular event or incident.
-
E.
burnedDuring
Indicates that one event, object, or process was actively burning or being consumed by fire during the time span of another specified event or interval.
- 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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f71f8ee0688190bd025f27993452d3 |
completed | May 3, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69f71cc405c08190863565609a4c8499 |
completed | May 3, 2026, 10 a.m. |
Created at: April 28, 2026, 3:40 a.m.