Triple
T10833010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victoria Cross to Sergeant Ian McKay |
E255671
|
entity |
| Predicate | recipientRank |
P95970
|
FINISHED |
| Object | Sergeant |
—
|
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: Sergeant | Statement: [Victoria Cross to Sergeant Ian McKay, recipientRank, Sergeant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: recipientRank Context triple: [Victoria Cross to Sergeant Ian McKay, recipientRank, Sergeant]
-
A.
rankingScope
Indicates the context or domain within which a ranking is defined, interpreted, or applied.
-
B.
rankedBy
Indicates that one entity is ordered or assigned a position in a hierarchy or list according to criteria determined or applied by another entity.
-
C.
peakRanking
Indicates the highest position or rank an entity has ever achieved within a specified ranking system or context.
-
D.
partnerRank
Indicates the relative status or level assigned to a partner within a partnership or collaboration hierarchy.
-
E.
attendanceRank
Indicates the relative position or level of an entity in terms of how frequently or consistently it attends compared to others.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7442439dc8190af59f9c8d0637c01 |
completed | April 9, 2026, 6:16 a.m. |
| PD | Predicate disambiguation | batch_69d70d25280c8190b648d7d1958b413a |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:19 p.m.