Triple
T27614582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOM |
E700405
|
entity |
| Predicate | honorsCategory |
P168087
|
FINISHED |
| Object | police decoration |
—
|
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: police decoration | Statement: [MOM, honorsCategory, police decoration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorsCategory Context triple: [MOM, honorsCategory, police decoration]
-
A.
honors
Indicates that one entity shows respect, recognition, or esteem toward another entity, often in a formal or ceremonial way.
-
B.
collegeHonors
Indicates that an individual has received formal academic honors or distinctions from a college.
-
C.
honorsActivity
Indicates that one entity formally recognizes, celebrates, or pays tribute to an activity or action performed by another entity.
-
D.
honorsSchool
Indicates that a school has received recognition, distinction, or special status for high achievement or excellence.
-
E.
honorsAspectOf
Indicates that one entity shows respect, recognition, or reverence specifically toward a particular aspect, quality, or facet of another entity.
- 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_69ef6a4f1d9c8190b0705acda054368d |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f673633d288190b52ceb9f8a057c44 |
completed | May 2, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 27, 2026, 2:12 p.m.