Triple
T33116771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabs of Afghanistan |
E847478
|
entity |
| Predicate | linguisticAssimilation |
P176396
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Arabs of Afghanistan, linguisticAssimilation, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticAssimilation Context triple: [Arabs of Afghanistan, linguisticAssimilation, high]
-
A.
languageOfAssimilation
Indicates the language used to integrate or absorb individuals or groups into a dominant culture or society.
-
B.
linguisticInfluence
Indicates that one entity has affected, shaped, or contributed to the language, style, or linguistic features of another entity.
-
C.
linguisticStrategy
Indicates the communicative approach or method used in language to achieve a particular interactional, rhetorical, or pragmatic goal.
-
D.
linguisticVariation
Indicates a relationship where one linguistic form differs from another in expression, usage, or structure while remaining related in meaning or function.
-
E.
culturalAssimilationInto
Indicates a process where one entity adopts or integrates into the cultural norms, values, and practices of another entity or group.
- 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_69f3495751a081909850af5843da40dc |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6e02ba6b881908dfafc52d3b75f1c |
completed | May 3, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_69f6de09c2f481909f8b2545d3208c9f |
completed | May 3, 2026, 5:32 a.m. |
| PDg | Predicate description generation | batch_69f6e029f0f88190b1f88d82a4a2cabd |
completed | May 3, 2026, 5:42 a.m. |
Created at: May 1, 2026, 1:27 a.m.