Triple
T3696367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mawenzi |
E78468
|
entity |
| Predicate | oneOfThreeMainVolcanicConesWith |
P49442
|
FINISHED |
| Object | Shira |
E78469
|
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: Shira | Statement: [Mawenzi, oneOfThreeMainVolcanicConesWith, Shira]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shira Context triple: [Mawenzi, oneOfThreeMainVolcanicConesWith, Shira]
-
A.
Shira
chosen
Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
-
B.
Sharya
Sharya is a town in Kostroma Oblast, Russia, known as a regional railway junction and logging center.
-
C.
Shera
Shera is the anthropomorphic tiger mascot created to represent and promote the 2010 Commonwealth Games held in Delhi, India.
-
D.
Tamina
The Tamina is a river in eastern Switzerland known for flowing through the deep Tamina Gorge before joining the Alpine Rhine.
-
E.
Kirsha
Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc50f9ad88190a926042fa73d65dc |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3d4821081909ccd1b5789eb761e |
completed | March 14, 2026, 2:11 a.m. |
Created at: March 8, 2026, 3:26 p.m.