Triple
T1005083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Cross |
E21689
|
entity |
| Predicate | firstAwardsMade |
P124
|
FINISHED |
| Object | 1941 |
—
|
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: 1941 | Statement: [George Cross, firstAwardsMade, 1941]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAwardsMade Context triple: [George Cross, firstAwardsMade, 1941]
-
A.
firstAwarded
chosen
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
B.
firstAwardedForFilm
Indicates the film for which an entity (such as a person or award) was first given or received an award.
-
C.
firstWinnerYear
Indicates the year in which an entity first won a particular competition, award, or title.
-
D.
firstCelebratedInYear
Indicates the year in which something (such as an event, holiday, or celebration) was first observed or celebrated.
-
E.
conflictOfFirstAwards
Indicates that there is a conflict or discrepancy between the initial awards or first recognitions associated with the related entities.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51303548190a5ee3c0797fc3245 |
completed | March 1, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b2e7108190b338b6c19d4aff55 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.