Triple
T5263739
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Town Hall (Neues Rathaus) Hanover |
E118887
|
entity |
| Predicate | hasLakeInFront |
P62621
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [New Town Hall (Neues Rathaus) Hanover, hasLakeInFront, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeInFront Context triple: [New Town Hall (Neues Rathaus) Hanover, hasLakeInFront, yes]
-
A.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
B.
hasLagoon
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
-
C.
usesLakeFor
Indicates that an entity utilizes a lake as a resource or setting for some purpose, activity, or function.
-
D.
hasMajorLake
Indicates that a geographic region or area contains at least one significant lake within its boundaries.
-
E.
hasWaterfrontPark
Indicates that a place or area includes or is associated with a park located directly along a body of water.
- 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd4a9888190a79ef8e64c764f86 |
completed | March 20, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69bd77c55224819096c0bcfcfae79bd3 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd7bcabe58819096255672664513b1 |
completed | March 20, 2026, 4:54 p.m. |
Created at: March 20, 2026, 1:51 p.m.