Triple
T1236811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nazareth Hospital (English Hospital) |
E26566
|
entity |
| Predicate | hasPatientDemographic |
P2263
|
FINISHED |
| Object | Arab citizens of Israel |
—
|
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: Arab citizens of Israel | Statement: [Nazareth Hospital (English Hospital), hasPatientDemographic, Arab citizens of Israel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPatientDemographic Context triple: [Nazareth Hospital (English Hospital), hasPatientDemographic, Arab citizens of Israel]
-
A.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
B.
hasDemographic
Indicates that an entity is associated with or characterized by a particular demographic group or attribute.
-
C.
demographicCharacteristic
Indicates that one entity specifies or describes a demographic attribute or feature (such as age, gender, ethnicity, or similar population-related trait) of another entity.
-
D.
demographicsLabel
chosen
Indicates the categorical demographic group or segment that an entity is associated with or classified under.
-
E.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf17e0bc8190a066561e6b629fc0 |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb67d52c8190815d6356b79d6ed5 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.