Triple
T8360238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohandessin |
E196988
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Imbaba |
E578153
|
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: Imbaba | Statement: [Mohandessin, adjacentTo, Imbaba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Imbaba Context triple: [Mohandessin, adjacentTo, Imbaba]
-
A.
Imbaba
chosen
Imbaba is a densely populated working-class district in the Giza Governorate of Greater Cairo, known for its informal urban development and vibrant local markets.
-
B.
Shamiya
Shamiya is a residential district in Kuwait City known for its planned layout, community facilities, and central location within the capital.
-
C.
Ibura
Ibura is a populous residential neighborhood and district located in the southern zone of Recife, Brazil.
-
D.
Shabara
Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
-
E.
Ibaan
Ibaan is a landlocked municipality in the province of Batangas in the Philippines, known for its agricultural economy and local religious and cultural festivities.
- 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_69ca82f2dbe48190aba982e75a0d94de |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80728eb081909bae6aae45848fab |
completed | March 31, 2026, 8:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cdc775a548819090c83d916b352f41 |
completed | April 2, 2026, 1:33 a.m. |
Created at: March 30, 2026, 6 p.m.