Triple
T15231838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deputy Lieutenant |
E364021
|
entity |
| Predicate | mayWearUniform |
P117665
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Deputy Lieutenant, mayWearUniform, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayWearUniform Context triple: [Deputy Lieutenant, mayWearUniform, true]
-
A.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
-
B.
woreUniformOf
Indicates that one entity was dressed in or used the official uniform associated with another entity (such as an organization, group, or role).
-
C.
hasSchoolUniform
Indicates that an entity is required to wear or is associated with a specific school uniform as part of its affiliation with a school.
-
D.
wearsUniformColor
Indicates that an entity regularly uses or is associated with a specific uniform color as part of its standard attire or dress code.
-
E.
wearsUniformSimilarTo
Indicates that one entity wears a uniform that is similar in appearance or style to the uniform worn by 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0078e27408190bc13c0ca441f5594 |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:12 a.m.