Triple
T30502885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Señor Ministro |
E776185
|
entity |
| Predicate | usedOrally |
P170234
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Señor Ministro, usedOrally, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOrally Context triple: [Señor Ministro, usedOrally, yes]
-
A.
isOralFormOf
Indicates that one entity is the oral (by-mouth) dosage form or version of another entity, typically a drug or medicinal product.
-
B.
isPrimarilyOral
Indicates that the primary mode of expression, communication, or transmission is spoken rather than written or signed.
-
C.
hasOralDiscFunction
Indicates that an entity possesses a specific functional role or capability associated with its oral disc.
-
D.
hasOralStops
Indicates that an entity possesses or exhibits oral stop consonant sounds in its phonological system.
-
E.
isOralCareRelated
Indicates that something is related to oral care, such as the maintenance, treatment, or hygiene of the mouth, teeth, or gums.
- 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_69f22498c5d481908aaea89e6fab8280 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 29, 2026, 8:15 p.m.