Triple
T18163733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYC Health + Hospitals/North Central Bronx |
E434832
|
entity |
| Predicate | hasLanguageAccess |
P123800
|
FINISHED |
| Object | multilingual services |
—
|
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: multilingual services | Statement: [NYC Health + Hospitals/North Central Bronx, hasLanguageAccess, multilingual services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageAccess Context triple: [NYC Health + Hospitals/North Central Bronx, hasLanguageAccess, multilingual services]
-
A.
hasLanguageStatus
Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
-
B.
hasHumanAccess
Indicates that a human is able to access, use, or interact with the referenced entity or resource.
-
C.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
D.
hasMemberLanguage
Indicates that one entity is a language that is a constituent or member of a larger language group, family, or collection represented by the other entity.
-
E.
hasLanguageResources
chosen
Indicates that an entity possesses or provides resources related to a particular language, such as tools, materials, or services supporting its use or study.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4dec419788190a999a68f32fab39b |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e4331baeb88190b21f50a98c36c78e |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.