Triple
T17263305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Félix Éboué |
E419058
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Cairo, Egypt |
E3705
|
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: Cairo, Egypt | Statement: [Félix Éboué, placeOfDeath, Cairo, Egypt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cairo, Egypt Context triple: [Félix Éboué, placeOfDeath, Cairo, Egypt]
-
A.
Cairo
chosen
Cairo is the capital and largest city of Egypt, a historic metropolis on the Nile renowned for its rich Islamic heritage and proximity to the ancient pyramids.
-
B.
Cairo
Cairo is a 2D graphics library that provides high-quality vector-based drawing capabilities for multiple output devices and backends.
-
C.
Cairo
Cairo is a 2D graphics library that provides high-quality vector-based drawing with support for multiple output backends such as image buffers, PDF, and SVG.
-
D.
Alexandria, Egypt
Alexandria, Egypt is a historic Mediterranean port city founded by Alexander the Great, renowned for its ancient library, lighthouse, and enduring cultural significance in Egypt.
-
E.
Sadat City
Sadat City is a planned industrial and residential city in Egypt, developed as part of the country’s strategy to create new urban centers and relieve population pressure on major metropolitan areas.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42f4379848190add32ba8e5f93527 |
completed | April 19, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0171041f2c81909bf52025d68912fc |
completed | May 11, 2026, 6:02 a.m. |
Created at: April 10, 2026, 5:40 a.m.