Triple
T18347274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hospital Clínico Regional de Concepción |
E439572
|
entity |
| Predicate | hasReferralRole |
P131456
|
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: [Hospital Clínico Regional de Concepción, hasReferralRole, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReferralRole Context triple: [Hospital Clínico Regional de Concepción, hasReferralRole, yes]
-
A.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
B.
hasContactRole
Indicates that an entity serves in a specific role or capacity as a contact for another entity.
-
C.
hasMarketingRole
Indicates that an entity holds a position or responsibility related to marketing activities within an organization.
-
D.
hasPartnershipRole
Indicates that an entity holds a specific role or function within a partnership relationship with another entity.
-
E.
hasFranchiseRole
Indicates that an entity holds a specific role or position within a franchise relationship.
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e514f594f88190a683e6224e091593 |
completed | April 19, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e4561d665081908ec555344e76d82b |
completed | April 19, 2026, 4:12 a.m. |
Created at: April 10, 2026, 10:37 a.m.