Triple
T31327878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ustersbach |
E798938
|
entity |
| Predicate | hasLocalBrewery |
P194425
|
FINISHED |
| Object |
Ustersbacher Brauerei
Ustersbacher Brauerei is a traditional German brewery based in Ustersbach, Bavaria, known for producing a range of regional beers.
|
E1955292
|
NE FINISHED |
How this triple was built (3 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: Ustersbacher Brauerei | Statement: [Ustersbach, hasLocalBrewery, Ustersbacher Brauerei]
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: Ustersbacher Brauerei Triple: [Ustersbach, hasLocalBrewery, Ustersbacher Brauerei]
Generated description
Ustersbacher Brauerei is a traditional German brewery based in Ustersbach, Bavaria, known for producing a range of regional beers.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalBrewery Context triple: [Ustersbach, hasLocalBrewery, Ustersbacher Brauerei]
-
A.
hasMajorBrewery
Indicates that a location or entity possesses or hosts a large, commercially significant brewery.
-
B.
hasBreweryScene
Indicates that a scene or event takes place in, or prominently features, a brewery.
-
C.
hasNearbyBrewery
Indicates that one entity is located close to or in the vicinity of a brewery.
-
D.
hasIntegratedMicrobrewery
Indicates that an entity includes or contains a microbrewery as a built-in or internal component.
-
E.
hasBreweryFocus
Indicates that an entity (such as a business, product, or activity) is primarily oriented around, specialized in, or dedicated to breweries or brewing-related operations.
- F. None of above. chosen
Provenance (7 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_69f224e3238c8190b2291f50ea4962cd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2a1e4d45cc81909598e09f3ed77bbb |
completed | June 11, 2026, 2:32 a.m. |
| NEDg | Description generation | batch_6a2a284d81fc819097af9a3b70f9f356 |
completed | June 11, 2026, 3:15 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2a28ce1320819097156336ff1bfefd |
completed | June 11, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
| PDg | Predicate description generation | batch_69fd6f9a8bd881909983fe8f4cd0ba98 |
completed | May 8, 2026, 5:07 a.m. |
Created at: April 29, 2026, 9:16 p.m.