Triple
T30276864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erlenbach (ZH) |
E769970
|
entity |
| Predicate | hasTransportConnection |
P845
|
FINISHED |
| Object |
Lake Zurich shipping services
Lake Zurich shipping services is a passenger boat network operating on Lake Zurich in Switzerland, connecting lakeside towns and providing both public transport and leisure cruises.
|
E1908087
|
NE 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: Lake Zurich shipping services | Statement: [Erlenbach (ZH), hasTransportConnection, Lake Zurich shipping services]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lake Zurich shipping services Triple: [Erlenbach (ZH), hasTransportConnection, Lake Zurich shipping services]
Generated description
Lake Zurich shipping services is a passenger boat network operating on Lake Zurich in Switzerland, connecting lakeside towns and providing both public transport and leisure cruises.
Provenance (5 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f680d983608190a05ee341096d3c6c |
completed | May 2, 2026, 10:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a276efa89bc819092f1f25dbf7d15fd |
completed | June 9, 2026, 1:40 a.m. |
| NEDg | Description generation | batch_6a277100aec88190a76cb557ee344e29 |
completed | June 9, 2026, 1:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a277181f69881908d6875221a8386e8 |
completed | June 9, 2026, 1:50 a.m. |
Created at: April 29, 2026, 7:44 p.m.