Triple
T1428298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amr |
E30384
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Amru |
E30384
|
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: Amru | Statement: [Amr, hasVariantSpelling, Amru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amru Context triple: [Amr, hasVariantSpelling, Amru]
-
A.
Amreya
Amreya is a district within Egypt’s Alexandria region, known for its mix of industrial zones, residential areas, and proximity to the Mediterranean coast.
-
B.
Amr
chosen
Amr is a common Arabic male given name, often associated with historical and contemporary figures across the Arab world.
-
C.
Shimsha
Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
-
D.
Azim
Azim is the given name of Azim Premji, the Indian business tycoon and philanthropist known for leading Wipro and his extensive charitable work.
-
E.
Al Jumum
Al Jumum is a town and governorate in western Saudi Arabia, situated near the holy city of Mecca in the Makkah administrative region.
- 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_69a498fb823c8190a67ce4c4837e641a |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4d9575881908bb58598e5a80590 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad016930ec8190ab3900d6f40c4aa0 |
completed | March 8, 2026, 4:56 a.m. |
Created at: March 1, 2026, 8 p.m.