Triple
T2394413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Nasser |
E47614
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Aswan |
E11620
|
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: Aswan | Statement: [Lake Nasser, near, Aswan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aswan Context triple: [Lake Nasser, near, Aswan]
-
A.
Aswan
chosen
Aswan is a historic city in southern Egypt on the Nile River, known for its ancient temples, quarries, and the nearby Aswan High Dam.
-
B.
Ismailia
Ismailia is a city in northeastern Egypt on the west bank of the Suez Canal, known for its strategic location, colonial-era architecture, and role as an administrative center for the canal zone.
-
C.
Assiut
Assiut is a major city in Upper Egypt on the Nile River, serving as an important regional administrative, commercial, and transportation hub.
-
D.
Tanta
Tanta is a major city in northern Egypt that serves as an important commercial and transportation hub in the Nile Delta.
-
E.
Dongola
Dongola is a historic town in northern Sudan that served as a major political and cultural center of medieval Nubian kingdoms along the Nile.
- 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_69a88a1c450c81909f61abb8b6863885 |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abc87827d88190bb2351a688e6de32 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6540028c8190aaafeada529d2e6a |
completed | March 10, 2026, 12:26 a.m. |
Created at: March 4, 2026, 7:57 p.m.