Triple
T21985772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurghada Port |
E542956
|
entity |
| Predicate | category |
P87
|
FINISHED |
| Object | Hurghada |
—
|
NE NERFINISHED |
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: Hurghada | Statement: [Hurghada Port, category, Hurghada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hurghada Context triple: [Hurghada Port, category, Hurghada]
-
A.
Hurghada
chosen
Hurghada is a major Egyptian Red Sea resort city known for its beaches, diving, and tourism industry.
-
B.
Sharm El Sheikh
Sharm El Sheikh is a popular Egyptian resort city on the southern tip of the Sinai Peninsula, known for its Red Sea beaches, coral reefs, and diving.
-
C.
Dahab
Dahab is a small Egyptian resort town on the southeast coast of the Sinai Peninsula, known for its laid-back atmosphere, diving spots, and windsurfing.
-
D.
Marsa Alam
Marsa Alam is a coastal Egyptian resort town on the western shore of the Red Sea, known for its diving sites, coral reefs, and relatively undeveloped beaches.
-
E.
Zagazig
Zagazig is a city in Egypt’s Nile Delta that serves as an important regional center for agriculture, education, and transportation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12709cb288190a2620e337fea364c |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:04 p.m.