Triple
T18013546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Bayda |
E430942
|
entity |
| Predicate | alternativeName |
P39
|
FINISHED |
| Object | El Beida |
—
|
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: El Beida | Statement: [Al-Bayda, alternativeName, El Beida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: El Beida Context triple: [Al-Bayda, alternativeName, El Beida]
-
A.
El Beida
chosen
El Beida is a city commonly known as Al Bayda, located in eastern Libya and serving as an important regional administrative and commercial center.
-
B.
El Azbakeya
El Azbakeya is a historic district in central Cairo known for its cultural landmarks, markets, and longstanding role as an urban hub of the city.
-
C.
Dar al-Maaref
Dar al-Maaref is an Egyptian publishing house known for issuing influential Arabic literary and cultural works.
-
D.
Madarihat
Madarihat is a small town in West Bengal, India, known primarily as the main gateway and service hub for visitors to Jaldapara National Park.
-
E.
Dar al-Wasaa
Dar al-Wasaa is a town located in Lebanon’s Baalbek-Hermel Governorate, a predominantly rural and agricultural region in the country’s northeast.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b521befc81908dff44f19aa3d580 |
completed | April 19, 2026, 10:57 a.m. |
Created at: April 10, 2026, 10:24 a.m.