Triple
T38434413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al Bani Bishr |
E903900
|
entity |
| Predicate | countryTraditionallyAssociatedWith |
P135536
|
FINISHED |
| Object | Saudi Arabia |
E6608
|
NE 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: Saudi Arabia | Statement: [Al Bani Bishr, countryTraditionallyAssociatedWith, Saudi Arabia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryTraditionallyAssociatedWith Context triple: [Al Bani Bishr, countryTraditionallyAssociatedWith, Saudi Arabia]
-
A.
countryInTradition
chosen
Indicates that a country participates in, is associated with, or belongs to a particular cultural, historical, or religious tradition.
-
B.
countryOfNamingTradition
Indicates the country whose cultural or linguistic naming conventions are used to form or interpret a given name.
-
C.
countryFA
Indicates that a country is the foreign affiliation or foreign authority associated with another entity.
-
D.
traditionalCountry
Indicates that a country is characterized by long-established customs, cultural practices, and social norms that have been preserved over time.
-
E.
traditionalCountryIncludes
Indicates that a traditional or culturally defined country encompasses or contains a given subregion or area.
- F. None of above.
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_69f76e6a2024819081aa04f4932f89d2 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c903be48190a2fafa53d7d50d42 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41c29489a48190babb81059e78f2fa |
completed | June 29, 2026, 12:55 a.m. |
| PD | Predicate disambiguation | batch_6a037a1e32108190897356d6a7fed879 |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.