Triple
T13051709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USS Enterprise (NCC-1701) |
E327462
|
entity |
| Predicate | registryMarking |
P32310
|
FINISHED |
| Object | NCC-1701 on primary hull |
—
|
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: NCC-1701 on primary hull | Statement: [USS Enterprise (NCC-1701), registryMarking, NCC-1701 on primary hull]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registryMarking Context triple: [USS Enterprise (NCC-1701), registryMarking, NCC-1701 on primary hull]
-
A.
reportedMarks
Indicates that an entity has formally communicated or submitted the marks/grades of another entity (such as a student or assessment) to a relevant party or system.
-
B.
marksOn
Indicates that one entity bears visible signs, traces, or imprints that have been made or left by another entity.
-
C.
distinctiveMarking
chosen
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
D.
markingFeature
Indicates a feature that serves as a distinguishing mark or identifier associated with an entity.
-
E.
marque
Indicates that one entity is the brand or make associated with another entity, such as a product, vehicle, or manufactured item.
- 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98a9829b48190b23624b6b3df4600 |
completed | April 10, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69d9803aca4c8190b1015cd159cc47a9 |
completed | April 10, 2026, 10:56 p.m. |
Created at: April 9, 2026, 8:57 p.m.