Triple
T18307476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYC Health + Hospitals/Woodhull |
E438524
|
entity |
| Predicate | languageAccess |
P11734
|
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/Woodhull, languageAccess, multilingual services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAccess Context triple: [NYC Health + Hospitals/Woodhull, languageAccess, multilingual services]
-
A.
languageAccessImplication
Indicates that the availability or characteristics of language access (e.g., translation, interpretation, or linguistic support) lead to, enable, or influence a particular outcome, condition, or relationship between entities.
-
B.
languageRights
Indicates that certain individuals or groups are entitled to use, maintain, or receive services in a particular language under recognized rights or protections.
-
C.
languageProvision
chosen
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageIndependence
Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
-
E.
languageText
Indicates that a piece of text is expressed in, or associated with, a particular language.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021519a481908a9b6561946f1c65 |
completed | April 19, 2026, 4:25 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.