Triple
T37105642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HD 245409 |
E918832
|
entity |
| Predicate | hasMessageTypeReceived |
P200235
|
FINISHED |
| Object | digital interstellar radio message |
—
|
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: digital interstellar radio message | Statement: [HD 245409, hasMessageTypeReceived, digital interstellar radio message]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMessageTypeReceived Context triple: [HD 245409, hasMessageTypeReceived, digital interstellar radio message]
-
A.
hasReceiver
Indicates that an entity serves as the recipient or target of something provided, sent, or directed by another entity.
-
B.
hasMessageSender
Indicates that one entity is the sender or originator of a given message.
-
C.
hasResponderMessageCount
Indicates the number of messages sent by the responder in a given interaction or conversation.
-
D.
hasPeerReception
Indicates that an entity has been received, evaluated, or acknowledged by its peers, typically through review, critique, or professional recognition.
-
E.
hasKeyMessage
Indicates that one entity conveys, contains, or is associated with a primary or central message of 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff7bc112088190851501fb2a16103d |
completed | May 9, 2026, 6:24 p.m. |
| PD | Predicate disambiguation | batch_69ff7b45507c81909753866ad733601a |
completed | May 9, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69ff7bbfa4b08190b11e84861706b349 |
completed | May 9, 2026, 6:23 p.m. |
Created at: May 3, 2026, 4:14 p.m.