Triple
T13236688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star Wars (Strategic Defense Initiative) |
E315163
|
entity |
| Predicate | doctrineRelation |
P108660
|
FINISHED |
| Object | nuclear deterrence |
—
|
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: nuclear deterrence | Statement: [Star Wars (Strategic Defense Initiative), doctrineRelation, nuclear deterrence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: doctrineRelation Context triple: [Star Wars (Strategic Defense Initiative), doctrineRelation, nuclear deterrence]
-
A.
foreignRelation
Indicates that there exists a diplomatic or international relationship between one entity and another entity from a different country or jurisdiction.
-
B.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
C.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
D.
multipleRelation
Indicates that an entity is involved in more than one distinct relationship of the specified type with other entities.
-
E.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d56da008190af55da3a9e7ffd4d |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98c959ba08190adf29dc0c4e1fca6 |
completed | April 10, 2026, 11:49 p.m. |
Created at: April 9, 2026, 9:22 p.m.