Triple
T901745
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Zein al-Sharaf |
E19460
|
entity |
| Predicate | knownAs |
P39
|
FINISHED |
| Object | Queen Zein |
E19460
|
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: Queen Zein | Statement: [Queen Zein al-Sharaf, knownAs, Queen Zein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Queen Zein Context triple: [Queen Zein al-Sharaf, knownAs, Queen Zein]
-
A.
Queen Zein al-Sharaf
chosen
Queen Zein al-Sharaf was a prominent Jordanian queen and political figure known for her influential role in shaping modern Jordan and supporting social and constitutional reforms in the mid-20th century.
-
B.
Queen Bavmorda
Queen Bavmorda is the ruthless and power-hungry sorceress-queen who serves as the primary villain in the fantasy film "Willow."
-
C.
Basilissa Ouranon
Basilissa Ouranon is the Greek name for the Queen of Heaven, a revered celestial goddess figure associated with divine authority and the heavens.
-
D.
Zeb-un-Nissa
Zeb-un-Nissa was a Mughal princess and noted Persian-language poet renowned for her literary works and intellectual pursuits in 17th-century India.
-
E.
Queen Red
Queen Red was one of the designated assault sub-sectors of Sword Beach used by Allied forces during the D-Day landings in World War II.
- 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_69a4939e889c8190ac148b3ac1a7f90b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad4412408190a6bf8fc7484a5781 |
completed | March 1, 2026, 9:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7c734e680819098840e9c736b5ead |
completed | March 4, 2026, 5:46 a.m. |
Created at: March 1, 2026, 7:39 p.m.