Triple
T29976041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beekeeper (Ronald Fischer, Beekeeper) |
E761447
|
entity |
| Predicate | hasModelName |
P192709
|
FINISHED |
| Object | Ronald Fischer |
—
|
NE NERFINISHED |
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: Ronald Fischer | Statement: [Beekeeper (Ronald Fischer, Beekeeper), hasModelName, Ronald Fischer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasModelName Context triple: [Beekeeper (Ronald Fischer, Beekeeper), hasModelName, Ronald Fischer]
-
A.
hasModelType
Indicates that an entity is associated with or classified under a specific model type.
-
B.
hasModelLine
Indicates that an item, product, or entity belongs to or is associated with a particular model line or series.
-
C.
hasModeName
Indicates that an entity is associated with a specific mode identified by a particular name.
-
D.
hasComponentName
Indicates that an entity includes or is associated with a component identified by a specific name.
-
E.
hasLocalModel
Indicates that one entity possesses or uses a model that is stored or executed locally rather than accessed remotely.
- 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_69f22467626081908d5afea489590e96 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
| PDg | Predicate description generation | batch_69fd28379d2c8190903ba228ee1cc756 |
completed | May 8, 2026, 12:03 a.m. |
Created at: April 29, 2026, 6:33 p.m.