Triple
T8118448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Capra Achievement Award |
E189538
|
entity |
| Predicate | honorsContributionType |
P35712
|
FINISHED |
| Object | production management |
—
|
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: production management | Statement: [Frank Capra Achievement Award, honorsContributionType, production management]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorsContributionType Context triple: [Frank Capra Achievement Award, honorsContributionType, production management]
-
A.
recognizesContributionType
chosen
Indicates that an entity acknowledges or identifies a specific type or category of contribution made by another entity.
-
B.
honorsAspectOf
Indicates that one entity shows respect, recognition, or reverence specifically toward a particular aspect, quality, or facet of another entity.
-
C.
honourType
Indicates the specific category or classification of an honour or award associated with an entity.
-
D.
honors
Indicates that one entity shows respect, recognition, or esteem toward another entity, often in a formal or ceremonial way.
-
E.
honorsRole
Indicates that one entity formally recognizes and respects the position, title, or role held by another entity.
- 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_69ca82baad008190ab2859712b9b1607 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4664fef881908b0dc7b158aca398 |
completed | March 31, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69cb368e7f4c81909aabd7716f0de79d |
completed | March 31, 2026, 2:50 a.m. |
Created at: March 30, 2026, 5:33 p.m.