Triple
T1062479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stardust |
E22936
|
entity |
| Predicate | isFrequentlyRecorded |
P22990
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Stardust, isFrequentlyRecorded, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isFrequentlyRecorded Context triple: [Stardust, isFrequentlyRecorded, true]
-
A.
performedFrequency
Indicates how often an action or activity is carried out within a given time period.
-
B.
frequentlyVisitedBy
Indicates that an entity is regularly or often visited by another entity.
-
C.
recorded
Indicates that one entity captured, stored, or documented information, audio, video, or data about another entity or event.
-
D.
recordedFor
Indicates that something has been documented, captured, or logged on behalf of or in association with a particular entity or context.
-
E.
historicallyRecordedSince
Indicates that the existence, occurrence, or recognition of one entity has been documented in historical records starting from the time specified by another entity.
- 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8f68a54819084326d87c3498252 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b7359eb881909c868a558861cc18 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b7da38888190a118ef20ce4ae9aa |
completed | March 1, 2026, 10:04 p.m. |
Created at: March 1, 2026, 7:42 p.m.