Triple
T5157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ismail Serageldin |
E101
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
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.
|
E390
|
NE FINISHED |
How this triple was built (4 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: Giza | Statement: [Ismail Serageldin, birthPlace, Giza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Giza Context triple: [Ismail Serageldin, birthPlace, Giza]
-
A.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
B.
Dædalus
Dædalus is a scholarly journal of the American Academy of Arts and Sciences that features interdisciplinary essays on culture, science, public affairs, and the arts.
-
C.
Joseph
Joseph is the first name of J. C. R. Licklider, a pioneering computer scientist often regarded as a key figure in the development of the internet and interactive computing.
-
D.
Washington Monument
The Washington Monument is a towering white marble obelisk on the National Mall that honors George Washington, the first president of the United States.
-
E.
Carnegie
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Giza Triple: [Ismail Serageldin, birthPlace, Giza]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Giza Target entity description: 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.
-
A.
Veritas
Veritas is the Latin word for "truth" and is famously used as the motto of Harvard University.
-
B.
Dædalus
Dædalus is a scholarly journal of the American Academy of Arts and Sciences that features interdisciplinary essays on culture, science, public affairs, and the arts.
-
C.
Joseph
Joseph is the first name of J. C. R. Licklider, a pioneering computer scientist often regarded as a key figure in the development of the internet and interactive computing.
-
D.
Washington Monument
The Washington Monument is a towering white marble obelisk on the National Mall that honors George Washington, the first president of the United States.
-
E.
Carnegie
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
- F. None of above. chosen
Provenance (5 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_69a23d871f1081909f1690b0fdf5afd0 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69a23f93f3488190ba464dc9f36c837f |
completed | Feb. 28, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a23fff6a588190b64366758e5f1c4f |
completed | Feb. 28, 2026, 1:08 a.m. |
Created at: Feb. 28, 2026, 12:40 a.m.