Triple
T23554890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khalafawy |
E578156
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Shubra |
—
|
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: Shubra | Statement: [Khalafawy, locatedIn, Shubra]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shubra Context triple: [Khalafawy, locatedIn, Shubra]
-
A.
Shubra
chosen
Shubra is a densely populated urban district in northern Cairo, Egypt, known for its vibrant commercial streets and diverse residential neighborhoods.
-
B.
Nabha
Nabha is a historic town in the Indian state of Punjab, known for its former princely state status and cultural heritage.
-
C.
Sabaria
Sabaria is the ancient Roman name for the city now known as Szombathely in western Hungary, historically significant as a provincial center in Pannonia.
-
D.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
E.
Shoba
Shoba was an acclaimed Indian film actress known for her powerful performances in Malayalam and Tamil cinema, whose promising career was cut short by her tragic death at a young age.
- 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_69e245fa93448190919cb04534560542 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1aed253788190ba75109af0e91b37 |
completed | April 29, 2026, 7:10 a.m. |
Created at: April 17, 2026, 6:12 p.m.