Triple
T21604807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federation Star |
E533142
|
entity |
| Predicate | pointCountHistory |
P7181
|
FINISHED |
| Object | originally six-pointed |
—
|
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: originally six-pointed | Statement: [Federation Star, pointCountHistory, originally six-pointed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointCountHistory Context triple: [Federation Star, pointCountHistory, originally six-pointed]
-
A.
previousRecordPoints
Indicates that one record directly precedes and connects to another record in a sequence or history.
-
B.
hasNumberOfPoints
chosen
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
C.
estimatedHistory
Indicates that there is an inferred or approximated record of past states, events, or values associated with an entity or relationship.
-
D.
pixelCount
Indicates the total number of individual pixels that make up a given image or visual element.
-
E.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
- 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.