Triple
T103131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Medicine |
E2082
|
entity |
| Predicate | reasonForNickname |
P7596
|
FINISHED |
| Object | prominence in healthcare |
—
|
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: prominence in healthcare | Statement: [City of Medicine, reasonForNickname, prominence in healthcare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForNickname Context triple: [City of Medicine, reasonForNickname, prominence in healthcare]
-
A.
nameChangeReason
Indicates the reason or justification for a change in an entity’s name.
-
B.
honorificNickname
Indicates that one entity is referred to by a respectful or honorific nickname by another entity or in a given context.
-
C.
nameOf
Indicates that one entity is the name or designation of another entity.
-
D.
usedPseudonym
Indicates that an entity performed an action or participated in a context under a name that was not their real or primary identity.
-
E.
athleticsNickname
Indicates the commonly used nickname or moniker for an entity’s athletics team or sports program.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2563a6ff48190bec582fb2f99b7af |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a258de46888190835db2b21a093eaa |
completed | Feb. 28, 2026, 2:54 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.