Triple
T11263590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lichtenburg |
E266624
|
entity |
| Predicate | toponymClass |
P17163
|
FINISHED |
| Object | habitation name |
—
|
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: habitation name | Statement: [Lichtenburg, toponymClass, habitation name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toponymClass Context triple: [Lichtenburg, toponymClass, habitation name]
-
A.
typeOfToponym
chosen
Indicates the specific category or kind of place name (toponym) that applies to a given geographic entity.
-
B.
isToponymic
Indicates that something is related to or derived from a place name (a toponym).
-
C.
hasTypeOfToponym
Indicates that one entity is classified as a specific type or category of toponym (place name) in relation to another entity.
-
D.
toponymRefersTo
Indicates that a place name (toponym) designates or refers to a specific geographic entity or location.
-
E.
hasToponymy
Indicates a relationship where one entity possesses or is associated with the system, study, or set of place names (toponyms) of another entity.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94d56048190bf808e1bc2188714 |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d7879bc56c8190b2e8d2193f29de05 |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:31 p.m.