Triple
T374511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the British Empire |
E8339
|
entity |
| Predicate | includesHonoraryAwardsFor |
P13060
|
FINISHED |
| Object | foreign nationals |
—
|
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: foreign nationals | Statement: [Order of the British Empire, includesHonoraryAwardsFor, foreign nationals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesHonoraryAwardsFor Context triple: [Order of the British Empire, includesHonoraryAwardsFor, foreign nationals]
-
A.
hasNotableHonoree
Indicates that an entity is notably dedicated to, named after, or honors a particular person or group.
-
B.
relatedAward
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
C.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
D.
honors
Indicates that one entity shows respect, recognition, or esteem toward another entity, often in a formal or ceremonial way.
-
E.
yearHonored
Indicates the specific year in which an entity received an honor, award, or formal recognition.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec13b9b48190b294d998c6720132 |
completed | Feb. 28, 2026, 1:22 p.m. |
| PD | Predicate disambiguation | batch_69a2e96216048190873ae533fa5b864d |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ebcb1b2c8190a68bb3bad600c227 |
completed | Feb. 28, 2026, 1:21 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.