Triple
T14250963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Thurgau |
E353258
|
entity |
| Predicate | hasLakePort |
P113404
|
FINISHED |
| Object | Romanshorn on Lake Constance |
—
|
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: Romanshorn on Lake Constance | Statement: [canton of Thurgau, hasLakePort, Romanshorn on Lake Constance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakePort Context triple: [canton of Thurgau, hasLakePort, Romanshorn on Lake Constance]
-
A.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
B.
hasLakeName
Indicates that an entity (such as a lake or related feature) bears or is associated with a specific lake name.
-
C.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
D.
hasLagoon
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
-
E.
isInLake
Indicates that one entity is located within the body of water defined as a lake.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6296f9d0819086f62f525d07eb12 |
completed | April 14, 2026, 3:51 p.m. |
| PD | Predicate disambiguation | batch_69de05c09b7881908acbca18bd7d997c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239bd0f48190ada38c0261e0ef3c |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:08 a.m.