Triple
T18370569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bajorans |
E446170
|
entity |
| Predicate | facialFeature |
P125456
|
FINISHED |
| Object | nose ridges |
—
|
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: nose ridges | Statement: [Bajorans, facialFeature, nose ridges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: facialFeature Context triple: [Bajorans, facialFeature, nose ridges]
-
A.
facialMarkings
chosen
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
-
B.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
C.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
D.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
E.
faceliftFeature
Indicates that one entity is a specific feature, component, or aspect involved in a facelift procedure or facelift-related modification of the other entity.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e5175324e48190a00572e15423feb7 |
completed | April 19, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:44 a.m.