Triple
T21604811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federation Star |
E533142
|
entity |
| Predicate | pointNumberStandardized |
P55022
|
FINISHED |
| Object | 1908 |
—
|
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: 1908 | Statement: [Federation Star, pointNumberStandardized, 1908]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointNumberStandardized Context triple: [Federation Star, pointNumberStandardized, 1908]
-
A.
pointDefinition
Indicates that one entity serves as the defining description or specification of a particular point in another entity.
-
B.
hasNumberOfPoints
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
C.
KPoint
Indicates a relationship where a specific point is designated or identified as a key or reference point within a spatial or geometric context.
-
D.
positionNumber
chosen
Indicates the specific ordinal or identifying number assigned to a position within an ordered set or organizational structure.
-
E.
pointsSource
Indicates that one entity serves as the origin or source from which points (such as scores, credits, or coordinates) are derived or assigned to another 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_69e0c46364608190a337dc8720dc2a35 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef17e4a8088190bf51ab2af2369762 |
completed | April 27, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69e69665fe8c8190af7e38785db188b2 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:33 p.m.