Triple
T12041974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nepomuk |
E286683
|
entity |
| Predicate | burnedDownIn |
P102908
|
FINISHED |
| Object | 1420 |
—
|
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: 1420 | Statement: [Nepomuk, burnedDownIn, 1420]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: burnedDownIn Context triple: [Nepomuk, burnedDownIn, 1420]
-
A.
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.
-
B.
burned
Indicates that one entity caused another entity to be damaged or consumed by fire or intense heat.
-
C.
burnsIn
Indicates that one entity undergoes combustion or is consumed by fire within or at the location of another entity.
-
D.
burningSince
Indicates that an object or substance has been continuously burning from a specified starting time up to the present or another reference time.
-
E.
burnsWhen
Indicates that one entity causes another entity to ignite or combust when they come into contact or under specified conditions.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
| PDg | Predicate description generation | batch_69d91006e14081909838412df082f794 |
completed | April 10, 2026, 2:58 p.m. |
Created at: April 8, 2026, 9:47 p.m.