Triple
T7184372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dizengoff Square |
E167531
|
entity |
| Predicate | hasCommonLanguageEnvironment |
P8383
|
FINISHED |
| Object | Hebrew |
—
|
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: Hebrew | Statement: [Dizengoff Square, hasCommonLanguageEnvironment, Hebrew]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonLanguageEnvironment Context triple: [Dizengoff Square, hasCommonLanguageEnvironment, Hebrew]
-
A.
hasLanguageContext
chosen
Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
-
B.
coexistsWithLanguage
Indicates that one entity exists or functions alongside a particular language at the same time, without excluding or replacing it.
-
C.
hasLanguageGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular language group.
-
D.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
E.
hasUnicodeStandard
Indicates that something conforms to, is defined by, or is associated with a particular version or aspect of the Unicode standard.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.