Triple
T25186666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enterprise NX-01 |
E630735
|
entity |
| Predicate | medicalOfficerSpecies |
P158008
|
FINISHED |
| Object | Denobulan |
—
|
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: Denobulan | Statement: [Enterprise NX-01, medicalOfficerSpecies, Denobulan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medicalOfficerSpecies Context triple: [Enterprise NX-01, medicalOfficerSpecies, Denobulan]
-
A.
memberSpecies
Indicates that a particular species is a constituent or member of a larger biological or taxonomic group.
-
B.
speciesType
Indicates the specific biological species category to which an entity belongs.
-
C.
studentSpecies
Indicates that one entity is a student whose biological species is identified by the other entity.
-
D.
hostSpecies
Indicates the species that serves as the host for another organism, agent, or entity.
-
E.
medicalBackground
Indicates that an entity has a history of prior medical conditions, treatments, or health-related experiences relevant to its current state or context.
- 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_69e75a8a6d088190ba1e82a4345225e7 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f46e0aeb588190b3ee13a6c031c223 |
completed | May 1, 2026, 9:10 a.m. |
| PD | Predicate disambiguation | batch_69f44d8043b081908bbffd7f044b4f26 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 21, 2026, 12:44 p.m.