Triple
T5728550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noor al-Hussein |
E126325
|
entity |
| Predicate | citizenship |
P2
|
FINISHED |
| Object | Jordan |
E11658
|
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: Jordan | Statement: [Noor al-Hussein, citizenship, Jordan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jordan Context triple: [Noor al-Hussein, citizenship, Jordan]
-
A.
Jordan
chosen
Jordan is a Middle Eastern country located at the crossroads of Asia, Africa, and Europe, known for its ancient archaeological sites like Petra and its strategic political role in the region.
-
B.
Jordan
Jordan is a popular Nike-owned athletic footwear and apparel brand originally inspired by basketball legend Michael Jordan and known for its iconic Air Jordan sneakers.
-
C.
Jordan
Jordan is a common given name used by people of all genders in many English-speaking and other countries.
-
D.
Jordan
Jordan is a municipality in the Philippines that serves as the capital of the island province of Guimaras in the Western Visayas region.
-
E.
ערבה
ערבה היא בקעה מדברית רחבת ידיים בדרום ארץ ישראל וירדן, המשתרעת בין ים המלח למפרץ אילת.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0250d5f4c8190a36b43ef5e6c7837 |
completed | March 22, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a1d7af8819092e28ce9fb14d1f1 |
completed | March 22, 2026, 9:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.