Triple
T13379446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jewish Israelis |
E319274
|
entity |
| Predicate | faceInternalDiversityIn |
P109695
|
FINISHED |
| Object | ethnicity |
—
|
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: ethnicity | Statement: [Jewish Israelis, faceInternalDiversityIn, ethnicity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceInternalDiversityIn Context triple: [Jewish Israelis, faceInternalDiversityIn, ethnicity]
-
A.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
B.
facesChallenge
Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
-
C.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
D.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
E.
numberOfFaces
Indicates the relationship that specifies how many faces a given object or entity has.
- F. None of above. chosen
Provenance (4 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadce56c6c8190adf4e19f6d1bc233 |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a03189908190a784a2755f8d81e1 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:33 p.m.