Triple
T2194393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the October Revolution |
E49936
|
entity |
| Predicate | awardedForCivilMerit |
P1472
|
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: [Order of the October Revolution, awardedForCivilMerit, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: awardedForCivilMerit Context triple: [Order of the October Revolution, awardedForCivilMerit, true]
-
A.
isCivilianAward
chosen
Indicates that an award is designated for civilians rather than military or combat-related recipients.
-
B.
secondHighestCivilianAwardIn
Indicates that an entity is the second highest-ranking civilian award conferred within a specified country or jurisdiction.
-
C.
militaryAward
Indicates that an entity has received or been granted a specific military honor, decoration, or award.
-
D.
peacetimeAward
Indicates that an award or honor is given during a period of peace rather than during wartime or active conflict.
-
E.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf74147c81908793c3694894f94a |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda52328819089c7ab111bebb0ca |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.