Triple
T27516117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pediatric Oncology Department at Johns Hopkins Children’s Center |
E694565
|
entity |
| Predicate | languageOfCare |
P741
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Pediatric Oncology Department at Johns Hopkins Children’s Center, languageOfCare, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCare Context triple: [Pediatric Oncology Department at Johns Hopkins Children’s Center, languageOfCare, English]
-
A.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
B.
languageOfProvision
Indicates the language in which a provision, such as a legal or contractual clause, is written or officially expressed.
-
C.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
D.
languageOfCoverage
Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
-
E.
languagesSpoken
chosen
Indicates that an entity is able to communicate using one or more specified languages.
- 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_69ef53842afc8190ba6bd4e4999bda67 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
Created at: April 27, 2026, 1:18 p.m.