Triple
T9539300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippsburg |
E230104
|
entity |
| Predicate | fortificationsDemolished |
P10256
|
FINISHED |
| Object | 18th century |
—
|
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: 18th century | Statement: [Philippsburg, fortificationsDemolished, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fortificationsDemolished Context triple: [Philippsburg, fortificationsDemolished, 18th century]
-
A.
demolishedOriginalStructures
Indicates that one entity has completely destroyed or removed the original structures associated with another entity.
-
B.
demolishedWith
Indicates that one entity was destroyed or torn down using another specified tool, method, or agent.
-
C.
demolishedAfter
Indicates that one entity was demolished at a point in time later than the demolition of another entity.
-
D.
mostStructuresDemolished
Indicates that the subject is the entity responsible for demolishing the greatest number of structures within a given context or set.
-
E.
demolished
chosen
Indicates that one entity completely destroyed or razed another entity, typically a structure or object, so that it no longer exists in its previous form.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e4df6c8190a4d1160c42daa45f |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.