Triple
T27077892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D.O. |
E685511
|
entity |
| Predicate | professionalAbbreviation |
P48372
|
FINISHED |
| Object | D.O. |
—
|
NE NERFINISHED |
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: D.O. | Statement: [D.O., professionalAbbreviation, D.O.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalAbbreviation Context triple: [D.O., professionalAbbreviation, D.O.]
-
A.
professionalTitleAbbreviation
chosen
Indicates that one entity is an abbreviated form of a professional title associated with another entity.
-
B.
professionalName
Indicates the formal name or title an entity uses in a professional or occupational context.
-
C.
academicTitleAbbreviation
Indicates that one entity is the standard abbreviated form of another entity’s full academic title.
-
D.
refersToWorkTitleAbbreviationOf
Indicates that one entity refers to a work by using an abbreviated form of that work’s title.
-
E.
professionalEquivalentTo
Indicates that two entities hold roles or positions that are considered professionally equivalent in status, function, or qualification.
- 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_69ef14843b1481909d828b3d5a44550a |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 27, 2026, 8:32 a.m.