Triple
T34183872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Azza |
E876901
|
entity |
| Predicate | hasHealthProvider |
P40116
|
FINISHED |
| Object | UNRWA clinics |
—
|
NE NERFINISHED |
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: UNRWA clinics | Statement: [Al-Azza, hasHealthProvider, UNRWA clinics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHealthProvider Context triple: [Al-Azza, hasHealthProvider, UNRWA clinics]
-
A.
hasHealthcareProvider
chosen
Indicates that one entity receives healthcare services or medical oversight from another entity acting as its healthcare provider.
-
B.
hasHealthcareServicesIn
Indicates that a healthcare provider or organization offers or operates healthcare services within a specified location or area.
-
C.
hasHealthPartner
Indicates that one entity is partnered with another to provide or manage health-related services, support, or benefits.
-
D.
hasHealthCareInstitutionType
Indicates that an entity is classified as a specific type or category of healthcare institution.
-
E.
hasHealthSystemLinkedTo
Indicates that one entity is connected or associated with a particular health system, typically for management, service provision, or administrative purposes.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: May 1, 2026, 1:55 a.m.