Triple
T6057367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butrus |
E134946
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Botros |
E24437
|
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: Botros | Statement: [Butrus, hasVariant, Botros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Botros Context triple: [Butrus, hasVariant, Botros]
-
A.
Butrus
Butrus is an alternative transliteration of the Arabic given name "Boutros," itself derived from "Peter."
-
B.
Boutros
chosen
Boutros is a male given name of Middle Eastern origin, notably borne by former UN Secretary-General Boutros Boutros-Ghali.
-
C.
Mohandessin
Mohandessin is a prominent, upscale district in Giza, Egypt, known for its residential neighborhoods, commercial avenues, and vibrant urban life.
-
D.
Dar Hussein
Dar Hussein is a historic palace in the Medina of Tunis, notable for its traditional Tunisian architecture and cultural significance.
-
E.
Mahmoud
Mahmoud is a common Arabic male given name widely used across the Middle East and Muslim-majority countries.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570d00e88190b2d8d596e40378d9 |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d0e06288190b4389b43825d5929 |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:09 p.m.