Triple
T1205541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Medal |
E25878
|
entity |
| Predicate | approximateTotalAwards |
P3160
|
FINISHED |
| Object | over 115000 during First World War |
—
|
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: over 115000 during First World War | Statement: [Military Medal, approximateTotalAwards, over 115000 during First World War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateTotalAwards Context triple: [Military Medal, approximateTotalAwards, over 115000 during First World War]
-
A.
numberOfAwards
chosen
Indicates the total count of awards that have been received by an entity.
-
B.
hasMultipleAwardsIndicatedBy
Indicates that an entity is recognized as having received multiple awards, as evidenced or signaled by a specified source or indicator.
-
C.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
D.
collectiveAwardsKnownAs
Indicates that a group of awards is commonly referred to by a particular collective name or title.
-
E.
mostAwardsHolder
Indicates that the subject is the entity that holds the highest number of awards within a given group or context.
- 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_69a4942b30f08190a91c60573e16b5ef |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bdc0f8d08190b340012a9eb26275 |
completed | March 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.