Triple
T24631986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal College of Emergency Medicine |
E609697
|
entity |
| Predicate | examinesForQualification |
P156843
|
FINISHED |
| Object | FRCEM |
—
|
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: FRCEM | Statement: [Royal College of Emergency Medicine, examinesForQualification, FRCEM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: examinesForQualification Context triple: [Royal College of Emergency Medicine, examinesForQualification, FRCEM]
-
A.
qualifyingFor
Indicates that one entity meets the necessary conditions or criteria to be eligible for another entity, status, or action.
-
B.
hasQualification
Indicates that an entity possesses a specific qualification, credential, or competency.
-
C.
hasQualificationCriteria
Indicates that there are specific conditions or standards that must be met for something to be considered eligible or acceptable.
-
D.
providedQualificationFor
Indicates that one entity supplied or granted a qualification, credential, or certification that another entity possesses or uses.
-
E.
determinedQualificationFor
Indicates that one entity has assessed and established another entity’s eligibility or suitability for a specific role, status, or requirement.
- 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_69e2c4d1d3708190a0f2dc6a3a8523bb |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f2be064ff88190b5d9e5ec75a41242 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6d0ab708190b2e3b94dd20ca76b |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:32 a.m.