Triple
T5155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ismail Serageldin |
E101
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Serageldin |
E101
|
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: Serageldin | Statement: [Ismail Serageldin, familyName, Serageldin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serageldin Context triple: [Ismail Serageldin, familyName, Serageldin]
-
A.
Ismail Serageldin
chosen
Ismail Serageldin is an Egyptian scholar and former vice president of the World Bank, best known as the founding director of the Bibliotheca Alexandrina and a prominent advocate for science, development, and cultural heritage.
-
B.
Avram
Avram is the given first name of Noam Chomsky, the influential American linguist, philosopher, and political activist.
-
C.
Edwin
Edwin is a masculine given name of Old English origin meaning "rich friend" or "prosperous friend."
-
D.
Theodor
Theodor "Ted" Nelson is an American pioneer of information technology best known for coining the term "hypertext" and envisioning global hyperlinked document systems.
-
E.
Giza
Giza is an Egyptian city on the west bank of the Nile, famous for the Giza Plateau where the Great Pyramids and the Sphinx are located.
- 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_69a238d6b47881909e68288aed2fd858 |
completed | Feb. 28, 2026, 12:37 a.m. |
| NER | Named-entity recognition | batch_69a2399d5cf88190998f9b95c817a60f |
completed | Feb. 28, 2026, 12:41 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a248d5b92481909a846984a8639067 |
completed | Feb. 28, 2026, 1:45 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.