Triple
T5136908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bruce the shark |
E115847
|
entity |
| Predicate | hasPropVersions |
P28478
|
FINISHED |
| Object | multiple mechanical models |
—
|
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: multiple mechanical models | Statement: [Bruce the shark, hasPropVersions, multiple mechanical models]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPropVersions Context triple: [Bruce the shark, hasPropVersions, multiple mechanical models]
-
A.
hasMultipleVersions
chosen
Indicates that an entity exists in more than one distinct version or revision.
-
B.
hasVersionIn
Indicates that one entity exists as a specific version or variant within the context, format, or system represented by another entity.
-
C.
hasVersionCount
Indicates the total number of distinct versions associated with a given entity.
-
D.
hasVersionType
Indicates that one entity is associated with a specific kind or category of version of another entity.
-
E.
haveProperty
Indicates that an entity possesses, exhibits, or is characterized by a particular property or attribute.
- F. None of above.
Provenance (3 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_69bd44459a988190a772a5c2ec6a1965 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7fef2e8c8190982dd67f50295ada |
completed | March 20, 2026, 5:12 p.m. |
| PD | Predicate disambiguation | batch_69bd77ac2fc48190abeebb003a82384c |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.